CN116959661A - Intelligent medicine taking management system - Google Patents
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Abstract
The invention discloses an intelligent medicine taking management system which comprises an intelligent terminal (1) and a cloud platform (2); the intelligent terminal (1) comprises a user side (3); the user terminal (3) comprises a login and registration module (31), a disease management module (32), a medicine management module (33), a medicine taking execution module (34) and an authorization module (35); the cloud platform (2) comprises a database (21), a data acquisition module (22), a data storage module (23), a data transmission module (24) and a data analysis module (25); the invention solves the problem that users take medicine randomly and take medicine by mistake due to unknown diseases through the management of the whole medicine taking process, and provides medicine taking reminding, medicine taking evaluation and medicine taking supervision functions.
Description
Technical Field
The invention relates to the technical field of intelligent medical treatment, in particular to an intelligent medicine taking management system.
Background
With the development of internet commercialization in recent years, the manner of online purchasing and online inquiry is gradually developed into a new trend, and the traditional manner of medicine administration management of doctors on patients cannot meet the increasing medical health service demands of people.
At present, many slow patients have various medicines and a large number of slow patients are basically middle-aged and elderly people, the complicated medicines can cause the problems of wrong medicine taking and disordered medicine taking of the patients, and the decline of memory can also cause the patients to take medicines in a missed way. At present, the management of taking medicine for the slow-speed patients of middle-aged and elderly people is basically that children are responsible for reminding, but the children can only ensure that the patients take medicine on time and cannot give more professional comments. In the same way, the doctor still has a very poor administration mode for the patient, even a lot of doctors and patients do not have administration measures, but the doctor lacks administration means and methods for the slow patient, and can not effectively and conveniently check and evaluate the administration condition of the patient, so that when the treatment effect of the patient is poor, the doctor can not accurately judge whether the administration link is problematic, and especially the administration of the slow patient by the doctor at home is harder.
In general, most people are used to purchasing medicines on the internet according to symptoms and experience of the people or non-professional search advice under the condition of unclear specific diseases, but often one symptom corresponds to the possibility of occurrence of various diseases, for example, headache and fever can correspond to hundreds of diseases such as cold, pharyngitis, rhinitis and intracranial infection, so that the phenomenon of medicine buying, medicine taking and the like can be caused by the so-called experience of people. In addition, most of the current e-commerce platforms directly recommend medicines through symptoms, but one symptom corresponds to multiple medicines, and the medicines are recommended when the multiple symptoms are input, so that the problem that a user cannot accurately select the medicines is also solved. Meanwhile, medicines are recommended in a professional mode as special commodities, and the medicines are recommended in a targeted mode according to different diseases, so that a user can be accurately and efficiently helped to find out the medicines meeting the requirements of the user, and relevant knowledge of the diseases and medication suggestions can be conveniently obtained. Therefore, the non-professional disease diagnosis and drug recommendation can lead to poor treatment effect of patients, and the phenomena of drug resistance, organ damage or poisoning can be seriously caused.
Disclosure of Invention
The invention aims to provide an intelligent medicine taking management system which comprises an intelligent terminal and a cloud platform.
The intelligent terminal comprises a user side.
The user terminal comprises a login and registration module, a disease management module, a medicine taking execution module and an authorization module.
The login and registration module is used for registering and verifying the identity of the user.
The disease management module is used for a user to search the name of the disease, add the disease and save the information of the suffering disease.
The medicine management module stores a personal medicine database, and the personal medicine database is used for storing medicine data added in a history mode.
According to the diseases added by the disease management module, medicines corresponding to the diseases are automatically matched, corresponding medicines are added to the personal medicine database, or the corresponding medicines are added to the personal medicine database through manual search of a user.
The medicine taking execution module makes and executes a medicine taking reminding plan according to the personal medicine data in the medicine management module.
When the intelligent medicine taking management system needs the user to provide private information, the authorization module acquires the corresponding personal private information of the user.
The cloud platform comprises a database, a data acquisition module, a data storage module, a data transmission module and a data analysis module.
The database comprises a disease library module, a symptom library module, a medicine library module, a pharmacy library module, a hospital library module and a doctor library module, wherein the modules are respectively used for storing a plurality of pieces of disease information, symptoms corresponding to each disease, a plurality of pieces of medicine information, a plurality of pieces of pharmacy information, a plurality of pieces of hospital information and a plurality of pieces of doctor information.
The data acquisition module is used for acquiring all data related in the database and storing the data into the database.
The data storage module is used for storing all data uploaded by the intelligent terminal.
The data transmission module is used for realizing information interaction between the intelligent terminal and the cloud platform or information interaction between the cloud platform and the outside.
The data analysis module comprises a retrieval screening module, an analysis module and a sequencing module.
The searching and screening module is used for searching the data in the database and transmitting the data to the analysis module.
The analysis module analyzes the data uploaded by the intelligent terminal and the data in the database, determines diseases and disease weights corresponding to user symptoms if intervention is performed, and a plurality of recommended medicines and medicine recommendation indexes and medicine similarity corresponding to each disease, and transmits the medicines and the weights to the sequencing module.
The sorting module performs descending order arrangement on the pre-suffering diseases according to the disease weights, performs descending order arrangement on the recommended medicines according to the medicine recommendation indexes and the medicine similarity, and transmits the arranged pre-suffering diseases and the recommended medicines to the intelligent terminal.
Further, the intelligent terminal further comprises an advisor terminal.
The consultant terminal comprises a login and registration module and a user information management module.
The login and registration module is used for registering and verifying the identity of the consultant.
The user information management module is used for displaying and managing information of users, and comprises a user personal information management module and a user medicine taking record information management module.
The user personal information management module is used for displaying and managing the user personal information from the user side.
The user medicine taking record information management module is used for displaying and managing the user medicine taking record information from the user side.
Further, the user side performs data interaction with the cloud platform.
And the advisor side performs data interaction with the cloud platform.
Further, the intelligent terminal further comprises a switching module.
The client, the advisor and the switching module are integrated in an integrated module.
And the user terminal and the advisor terminal are switched through a switching module.
Further, the user side also comprises an advisor management module, an incentive mechanism module and a personal information recording module.
The advisor management module is used for users to add advisors or view information of the added advisors.
The advisor management module comprises an advisor adding module, a relationship binding module and an advisor information management module.
The advisor adding module is used for adding the advisor.
The relation binding module is used for binding the relation between the user and the consultant. The relationship includes doctor-patient relationship and relatives and friends relationship. The relatives and friends include relatives and friends.
The advisor information management module is used for viewing the information of the added advisor.
And the incentive mechanism module executes rewards and punishments of points and/or pushes of positive and negative incentive information according to the information of the medicine taking condition recording module.
The incentive mechanism module comprises a plan execution evaluation module, an incentive mechanism setting module, an incentive mechanism execution module and an incentive mechanism execution recording module.
The plan execution evaluation module is used for evaluating the taking situation according to the taking situation recording module;
the incentive mechanism setting module is used for setting an incentive mechanism rule model by a user or an advisor and comprises an integral value setting unit, an execution mechanism time setting unit and an execution mechanism frequency setting unit.
The integral value setting unit, the execution mechanism time setting unit and the execution mechanism times setting unit are respectively used for setting the excitation integral value, the execution mechanism time and the execution mechanism times.
The excitation mechanism executing module is used for executing a corresponding excitation mechanism according to the evaluation result of the plan executing evaluation module and the mechanism rule set by the excitation mechanism setting module, and comprises an integral calculating module and an excitation information pushing module.
The point calculation module is used for executing rewards, deductions and calculation of points according to the evaluation result.
The excitation information pushing module is used for pushing excitation information to a user according to the data of the plan execution evaluation module, wherein the excitation information pushing comprises positive and negative information, and the pushing mode comprises but is not limited to popup window pushing and short message pushing;
the incentive mechanism execution recording module is used for storing the incentive mechanism execution record.
The personal information recording module comprises a basic information module, a physiological parameter information module and a behavior information module.
The information stored in the basic information module comprises one or more of gender, age, occupation, family genetic history, historical diseases and allergy history of the user.
The information stored in the physiological parameter information module comprises one or more of body temperature information, blood pressure information, blood glucose information, BMI, heart rate information and blood oxygen saturation information.
The information stored in the behavior information module comprises one or more of recent ingestion information, movement information, sleep information, smoking behavior information, drinking information and sexual behavior information of a user.
Further, the consultant side also comprises a professional certification module, a medicine taking plan making module and a guiding evaluation module.
The job certification module is used for registering and certifying the job by the consultant and comprises a job selection module, a job title level module, a duration module, an academic certificate module and a qualification certificate module.
The job selection module, the job ranking module, the practitioner duration module, the learning certificate module and the qualification certificate module are respectively used for recording the occupation, the job ranking, the practitioner duration, the learning certificate and the qualification certificate of the consultant.
The medicine taking plan making module is used for making a personalized medicine taking plan for a user and transmitting the personalized medicine taking plan to the user side.
The guiding evaluation module is used for inputting guiding evaluation results of the medicine taking behaviors of the user and transmitting the guiding evaluation results to the user side, and comprises an evaluation recording module and an evaluation report generating module.
The evaluation recording module is used for inputting the guiding evaluation result of the medicine taking behavior of the user.
And the evaluation report generating module generates an evaluation report according to the guiding evaluation result of the medicine taking behavior of the user and transmits the evaluation report to the user side.
Further, the disease management module comprises a disease inquiry module, a personal disease library module and a disease adding module.
The disease inquiry module comprises a disease classification inquiry module, a manual search inquiry module, a personal disease library inquiry module and a disease recommendation module;
the disease classification inquiry module is used for classifying and rapidly inquiring diseases according to the disease data of the disease library module and comprises a system classification unit, an organ classification unit, a department classification unit, an age classification unit and a gender classification unit;
the manual search query module is used for a user or a consultant to manually query diseases;
the personal disease library inquiry module is used for storing diseases which the user suffers from.
The disease recommending module is used for intelligently recommending possible diseases to a user and comprises a personal information record acquiring unit, an environment information acquiring unit and a disease matching unit, wherein the environment information acquiring unit comprises an area and weather information.
The personal disease library module is used for storing disease information of a user, including a disease information management module.
The disease information management module is used for a user to execute the operations of adding, deleting, checking and modifying the disease information.
The disease adding module is used for adding disease information.
The medicine management module comprises a medicine inquiry module, a personal medicine library module, a medicine adding module and a medicine buying recording module.
The medicine inquiry module comprises a medicine recommendation module, a medicine classification inquiry module, a manual search inquiry module, a personal medicine library inquiry module and a code scanning inquiry module.
And the medicine recommending module automatically performs matching recommendation on the medicines in the database according to the diseases added by the disease adding module.
The medicine recommending module comprises a disease information acquiring unit and a medicine matching unit.
The medicine classification inquiry module is used for rapidly inquiring medicines according to the medicine data in the medicine library module and comprises a brand classification unit, a dosage form classification unit, an age classification unit and a gender classification unit;
the manual search query module is used for manually inputting medicine name query by a user;
the personal medicine library inquiry module is used for inquiring in medicines added by a user;
the code scanning inquiry module is used for a user to scan the bar code on the medicine box to directly identify and inquire the medicine;
the disease information acquisition unit is used for acquiring the diseases added by the disease adding module.
The medicine matching unit is used for automatically matching and recommending medicines in the database.
The personal medicine library module is used for storing medicine information taken by a user.
The medicine adding module is used for adding medicines.
The medicine buying recording module is used for recording medicine information purchased by a user.
The medicine taking execution module comprises a medicine taking plan making module, a medicine taking plan execution module and a medicine taking condition recording module.
The medicine taking plan making module comprises a medicine information viewing module, a medicine taking state display module, a medicine taking plan setting module and an identity security verification module.
The medicine information viewing module is used for displaying medicine information.
The medication status display module includes a medication on-taking unit, a completion planning unit, and an accident suspension unit.
The on-taking unit, the completion planning unit and the accident suspension unit record the user taking record, the taking plan completion condition and the taking suspension condition respectively.
The medicine taking plan setting module is used for setting specific medicine taking parameters every day and comprises a medicine taking time setting unit, a medicine taking times setting unit, a medicine total quantity recording unit, a reminding time setting unit and a medicine buying reminding setting unit.
The identity security verification module is used for carrying out identity secondary verification when the user side or the consultant side enters the medicine taking plan making module. The identity secondary verification comprises one of a password authentication unit, a fingerprint authentication unit and a face authentication unit.
The medicine taking plan execution module is used for a user to execute a plan after making a medicine taking plan and comprises a medicine taking reminding module, an incentive information pushing module, a non-planned oral medicine taking selection module and an actual medicine taking time recording module.
The medicine taking reminding module is used for reminding a user to take medicine.
The incentive information pushing module is used for comparing the result of the difference between the taking time and the actual taking time formulated by the user with a preset value and pushing different incentive information.
The non-planned oral medicine selection module comprises a multi-service unit and a supplementary service unit.
The multi-taking unit is used for recording the situation of taking more medicines for users.
The supplementary service unit is used for recording the supplementary service condition of the user on the dew medicine.
The actual taking time recording module is used for recording the actual taking time of a user.
The medicine taking condition recording module is used for recording the medicine taking condition of a user.
Furthermore, the medicine taking plan making module further comprises a prescription uploading identification module, a plan prescription comparison analysis module and a warning module.
And the prescription uploading identification module is used for identifying and extracting characteristic points of the captured prescription information of the medicine by utilizing a related identification model algorithm after a user inputs and uploads the prescription.
The characteristic points comprise basic information of one or more medicines in the chemical names of the medicines, the medical preparation, the dosage, the specification and the usage of the medicines, and the basic information is transmitted to the plan prescription comparison module in the form of standardized text and/or digital content.
The plan prescription comparison analysis module is used for comparing and analyzing parameters in the medicine taking plan setting module and the prescription uploading identification module, and sending a warning signal to the warning module when the comparison and matching result is higher than a preset value.
And after receiving the warning signal, the warning module gives an alarm.
Further, the data transmission module further comprises an interface module, wherein the interface module is used for acquiring personal prescription data in the hospital system and transmitting the personal prescription data to the prescription uploading identification module;
the interface module is also used for providing an open interface for a specific unit so as to acquire the medicine taking record data of the user in the system.
Further, the analysis module comprises a disease recommendation analysis module, a drug recommendation analysis module and an advisor recommendation analysis module.
The disease recommendation analysis module comprises a standard vector establishment unit, a real-time data vector establishment unit, a vector comparison unit and a weight calculation unit.
The standard vector establishing unit establishes standard vectors according to the keywords in the disease library module and the symptom library moduleAnd transmitted to the vector contrast unit.
Wherein the method comprises the steps ofRepresenting symptom keywords entered by the user and corresponding data in the symptom library module. />Representing data corresponding to keywords in the personal information record module in the disease library module and the symptom library module.b n 、p n 、a n And the data corresponding to the keywords in the basic information module, the physiological parameter information module and the behavior information module in the disease library module and the symptom library module are respectively represented. Geographical climate information vector->r n 、w n And respectively representing the data corresponding to the keywords in the affiliated areas and the weather information in the disease library module and the symptom library module.
The real-time data vector establishing unit establishes a vector according to the real-time data in the personal information record acquiring unit and the environment information acquiring unit in the t timeAnd transmitted to the vector contrast unit. />Real-time data in the personal information recording and acquiring unit; />Real-time data in the environment information acquisition unit;
the vector comparison unit is used for receiving the data of the standard vector establishing unit and the real-time data vector establishing unit, and vector quantity And->Take intersection set, recorded as (g) 1 ,g 2 ,g 3 ,...g m ) And transmitted to the weight calculation unit.
m is a vectorAnd->Number of elements of the intersection;
the weight calculation unit calculates a scoreAnd transmitted to the sequencing module. />Representing a preset weight value for each datum. n=1, 2, …, m.
The medicine recommendation analysis module comprises a keyword extraction unit, a comprehensive calculation unit, a recommendation index calculation unit and a similarity calculation unit.
The keyword extraction unit is used for acquiring the disease data in the disease adding module, extracting the disease keywords in the drug library module and transmitting the disease keywords to the comprehensive calculation unit.
The comprehensive calculation unit is used for carrying out comprehensive weight calculation on the extracted keyword i, and the calculation formula is as followsWherein W is TP-IDF (i) TP-IDF weight value, W of key word p (i) The weight value is set according to the keywords and is transmitted to a recommendation index calculating unit. W (W) weight (i) Is the comprehensive weight;
the recommendation index calculation unit is used for calculating the recommendation index of the medicine according to the comprehensive weight of the keywords, and the recommendation index is recorded as score=d 1 ·W weight (i 1 )+d 2 ·W weight (i 2 )+d 3 ·W weight (i 3 )+...+d m ·W weight (i m )。(d 1 ,d 2 ,d 3 ,...d m ) Is a set of drug vectors. (W) weight (i 1 ),W weight (i 2 ),W weight (i 3 ),...W weight (i m ) A weight set corresponding to the drug vector set).
The similarity calculation unit is used for calculating the similarity of the medicines, selecting the first k medicines in a descending order according to the recommended index and the numerical value of the similarity, and transmitting the medicines to the ordering module. Wherein, the medicine similarity Wherein A and B are given different drug sets. When A, B is empty, J (A, B) is 1, and the medicines with higher recommendation indexes and similarity indexes are transmitted to the sorting module.
Further, the advisor adding module includes an advisor query module and an advisor recommendation module.
The advisor recommendation module is used for recommending the best advisor to the user according to the diseases added by the user and the information of the advisor, and comprises an advisor type selection unit, an advisor information acquisition unit and a recommendation index generation unit.
The result matrix B of the advisor type selection unit i ＝[B 1 ,B 2 ]Wherein B is 1 Representing doctor category, B 2 Representing a non-doctor class.
The advisor information acquisition is used for acquiring information from the professional authentication module, and comprises a job title level set C i ＝[C 1 ,C 2 ,C 3 ,...,C n ]Time duration of operation matrix D i ＝[D 1 ]Set of school certificates E i ＝[E 1 ,E 2 ,E 3 ,...,E n ]Set of qualification certificates F i ＝[F 1 ,F 2 ,F 3 ,...,F n ]。F n3 Representing the nth 3 qualificationA book; e (E) n2 Representing an nth 2 academic certificate; c (C) n1 Represents the n1 st job title level; d (D) 1 Representing a duration of a practitioner;
the recommendation index unit is used for generating a recommendation index according to the received data, and transmitting and displaying the recommendation index to the user side in descending order.
The step of generating the recommendation index by the recommendation index unit according to the received data comprises the following steps:
s1, the consultant recommending module receives information in a consultant type selecting unit, a job title level module, a time duration module, an academic certificate module and a qualification certificate module.
S2, acquiring data in the advisor type selection unit.
S3, if B i ＝B 1 Then generate a recommendation index Wherein C, E, F respectively represents the number, C ", D of elements in the job title level set, the academic certificate set, the qualification certificate set 1 ", E", F "are respectively expressed as reference title level number, reference practice duration, reference academic certificate number, reference qualification certificate number, < >>ω C 、/>ω E 、ω F Weighting factors respectively represented as a preset advisor type selection unit, a job ranking module (432), a duration of practise module (433), an academic certificate module (434), and a qualification certificate module (435);
if B i ≠B 1 Then generate a recommendation index Wherein->The weight factor is expressed as a preset friendship.
According to the invention, the traditional mode of recommending medicines according to simple fuzzy symptoms is changed into recommending medicines according to specific diseases, so that the professionality and accuracy of medicine recommendation are greatly improved, and the probability of no symptoms and messy medicine taking of users is reduced; and secondly, the user makes a medicine taking plan according to the selected medicine by himself or a consultant, and sets medicine taking reminding and medicine taking condition evaluation, so that the risk of medicine leakage is reduced. Moreover, the consultants at the consultant end of the system are not limited to professional staff, but also relatives and friends, the interaction function of the relatives and friends is added in the medicine taking action, and meanwhile, the medicine taking excitation mechanism is added, so that for chronic patients taking medicine for a long time, the medicine can be accurately taken, and the effect of more voluntarily taking medicine can be achieved.
The invention can lead the patient to carry out the medicine taking from the beginning of the definitely suffering disease to the end of the accurate execution, and carry out auxiliary evaluation guidance by the consultant terminal, systematically and comprehensively manage the whole medicine taking process of the patient, and can avoid the phenomena of medicine taking by mistake, medicine taking disorder and medicine taking missing of the patient.
The invention is provided with the consultant terminal, the consultant terminal checks the medicine taking execution condition of the patient through the patient information management module and timely gives out evaluation guidance advice, the consultant terminal can also execute planning operation aiming at the chronic disease patient, the problem that the chronic disease patient cannot make a medicine taking plan when the condition of the chronic disease patient is not allowed is considered, the consultant terminal can provide professional medicine advice for the patient and can play a supervision role, and the invention is particularly helpful for family doctors to manage the medicine taking problem of the chronic disease patient.
The consultant recommending module accurately recommends the consultants according to the diseases suffered by the users and the professional authentication conditions of the consultants; the setting has more accurate treatment effect on the diseases suffered by the user, and the consultant can play roles in supervising the taking of medicines, guiding the taking of medicines and evaluating the taking of medicines, and can be a medical care personnel or a relatives and friends. The conventional consultant adding mode is adopted by a user, and the adding mode is more suitable for the user to adopt an off-line medicine purchasing mode, and the on-line medicine purchasing mode cannot contact and add a professional consultant, so that the traditional mode does not enable the consultant to really play a role, and medical resources are wasted to a certain extent. According to the consultant recommendation module, the consultants can be recommended accurately according to the requirements of the user, and the requirements of the user on accurate medicine taking are met.
The medicine taking is used as a relatively non-positive execution event, the excitation mechanism module can excite the enthusiasm of taking medicine, especially the mutual excitation of relatives and friends, the excitation mechanism of the scheme has point rewards and positive feedback message push rewards, the user can automatically give rewards according to the execution condition when executing the medicine taking plan, and the user can obtain feedback of executing the medicine taking plan at the first time, so that the user can be helped to develop the habit of taking medicine on time, and the medicine taking behavior is not regarded as painful behavior any more.
Drawings
FIG. 1 is a schematic diagram of a system frame of the present invention, FIG. 1;
FIG. 2 is a schematic diagram of a database framework of the present invention;
FIG. 3 is a schematic diagram of a data analysis module framework according to the present invention;
FIG. 4 is a schematic diagram of a system frame of the present invention 2;
FIG. 5 is a schematic diagram of a user information management module framework according to the present invention;
FIG. 6 is a schematic diagram of a system frame of the present invention, FIG. 3;
FIG. 7 is a schematic diagram of a client side frame of the present invention;
FIG. 8 is a schematic diagram of an advisor management module of the present invention;
FIG. 9 is a schematic diagram of an excitation mechanism module framework of the present invention;
FIG. 10 is a schematic diagram of an actuator mechanism execution module framework of the present invention;
FIG. 11 is a schematic diagram of a personal information recording module framework according to the present invention;
FIG. 12 is a schematic diagram of an advisor end frame in accordance with the present invention;
FIG. 13 is a schematic diagram of a job certification module framework according to the present invention;
FIG. 14 is a schematic diagram of an evaluation guidance module framework according to the present invention;
FIG. 15 is a schematic diagram of a disease management module framework of the present invention;
FIG. 16 is a schematic diagram of a disease query module framework of the present invention;
FIG. 17 is a schematic diagram of a personal disease library module frame of the present invention;
FIG. 18 is a schematic diagram of a drug management module framework of the present invention;
FIG. 19 is a schematic diagram of a drug query module framework of the present invention;
FIG. 20 is a schematic diagram of a medication execution module frame of the present invention;
FIG. 21 is a schematic view of a frame of a medication planning module of the present invention 1;
FIG. 22 is a schematic diagram of a medication schedule execution module framework of the present invention;
FIG. 23 is a schematic view of a frame of a medication scheduling module of the present invention;
FIG. 24 is a schematic view of a frame of a medication scheduling module of the present invention;
FIG. 25 is a schematic diagram of a data transmission module frame according to the present invention;
fig. 26 is a schematic flow chart of a data transmission module according to the present invention;
FIG. 27 is a schematic diagram of an analysis module framework of the present invention;
FIG. 28 is a schematic diagram of an advisor add-on module framework of the present invention.
Detailed Description
The present invention is further described below with reference to examples, but it should not be construed that the scope of the above subject matter of the present invention is limited to the following examples. Various substitutions and alterations are made according to the ordinary skill and familiar means of the art without departing from the technical spirit of the invention, and all such substitutions and alterations are intended to be included in the scope of the invention.
Example 1:
referring to fig. 1 to 28, an intelligent medicine taking management system comprises an intelligent terminal 1 and a cloud platform 2.
The intelligent terminal 1 comprises a user terminal 3.
The client 3 includes a login registration module 31, a disease management module 32, a drug management module 33, a medication execution module 34, and an authorization module 35.
The login-registration module 31 is used for registering and verifying the identity of the user.
The disease management module 32 is used by the user to retrieve disease names, add diseases, and save information of the afflicted disease.
The medicine management module 33 stores a personal medicine database for holding historically added medicine data.
According to the diseases added by the disease management module 32, the medicines corresponding to the diseases are automatically matched, the corresponding medicines are added to the personal medicine database, or the corresponding medicines are added to the personal medicine database through manual search of a user.
The medication execution module 34 creates and executes a medication reminder plan based on the personal medication data in the medication management module 33.
When the intelligent medication management system requires the user to provide private information, the authorization module 35 obtains personal private information corresponding to the user.
The cloud platform 2 comprises a database 21, a data acquisition module 22, a data storage module 23, a data transmission module 24 and a data analysis module 25.
The database 21 includes a disease library module 211, a symptom library module 212, a drug library module 213, a pharmacy library module 214, a hospital library module 215, and a doctor library module 216, which are respectively used for storing a plurality of pieces of disease information, symptoms corresponding to each disease, a plurality of pieces of drug information, a plurality of pieces of pharmacy information, a plurality of pieces of hospital information, and a plurality of pieces of doctor information.
The data collection module 22 is configured to collect all data related to the database 21 and store the data in the database 21.
The data storage module 23 is configured to store all data uploaded by the intelligent terminal.
The data transmission module 24 is configured to implement information interaction between the intelligent terminal 1 and the cloud platform 2 or information interaction between the cloud platform 2 and the outside.
The data analysis module 25 includes a search screening module 251, an analysis module 252, and a ranking module 253.
The search screening module 251 is configured to search the data in the database 21 and transmit the data to the analysis module 252.
The analysis module 252 analyzes the data uploaded by the intelligent terminal 1 and the data in the database 21, determines the disease and the disease weight of the intervention corresponding to the user symptom, and the recommended medicines and the medicine recommendation indexes and the medicine similarity corresponding to each disease, and transmits the medicines and the medicine recommendation indexes and the medicine similarity to the sequencing module 253.
The sorting module 253 performs descending order of pre-disease according to the disease weight, performs descending order of recommended drugs according to the drug recommendation index and the drug similarity, and transmits the arranged pre-disease and recommended drugs to the intelligent terminal 1.
The use process of the intelligent medicine taking management system comprises the following steps:
step 1, a login registration module 31 selects a login account of a user side or a consultant side;
step 2, if the operation of the user terminal 3 is selected to be executed, the disease management module 32 performs disease inquiry and adds;
step 3, if the user terminal 3 operation is selected to be executed, the medicine management module 33 performs medicine recommendation according to the disease keywords in the disease adding module 323 or queries and adds medicines according to the medicine query module 331; if the advisor side 4 operation is selected to be executed, the planning module 43 plans the medicine taking plan for the patient and transmits the medicine taking plan to the user side;
step 4, if the user terminal 3 is selected to be executed, receiving a plan made by the advisor terminal 4 or manually adding a medicine taking plan and executing the plan; if the advisor 4 operation is selected, the patient information management module 41 looks at the patient medication records;
and step 5, if the consultant side 4 is selected to be operated, the patient takes the medicine, and the medicine is evaluated and guided through the guiding evaluation module 44 and is transmitted to the user side 3.
Example 2:
the technical content of the intelligent medicine taking management system is the same as that of the embodiment 1, and further, the intelligent terminal 1 further comprises an advisor terminal 4.
The advisor side 4 includes a login registration module 31 and a user information management module 41.
The login-registration module 31 is used to register and verify the advisor identity.
The user information management module 41 is used for displaying and managing information of users, and comprises a user personal information management module 411 and a user medicine taking record information management module 412.
The user personal information management module 411 is used for displaying and managing user personal information from the user terminal 3.
The user administration record information management module 412 is used for displaying and managing the user administration record information from the user terminal 3.
Example 3:
an intelligent medicine administration management system, the technical content of which is as in any one of embodiments 1-2, further, the user terminal 3 performs data interaction with the cloud platform 2.
The advisor side 4 performs data interaction with the cloud platform 2.
Example 4:
an intelligent medicine taking management system has the technical content as in any one of embodiments 1-3, and further, the intelligent terminal 1 further comprises a switching module 6.
The client 3, the advisor 4 and the switching module 6 are integrated in an integration module 5.
The client 3 and the advisor 4 are switched by a switching module 6.
Example 5:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 1-4, further, the client 3 further includes an advisor administration module 36, an incentive mechanism module 37, and a personal information record module 38.
The advisor management module 36 is used for users to add advisors or view information from an added advisor.
The incentive mechanism module 37 executes rewards and punishments of points and/or pushing of positive and negative incentive information according to the information of the medicine taking condition recording module 343.
The personal information recording module 38 includes a base information module 381, a physiological parameter information module 382, and a behavior information module 383.
Example 6:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 1-5, further, the advisor administration module 36 includes an advisor adding module 361, a relationship binding module 362, and an advisor information management module 363.
The advisor adding module 361 is configured to add advisors.
The relationship binding module 362 is used to bind relationships between users and advisors. The relationship includes doctor-patient relationship and relatives and friends relationship. The relatives and friends include relatives and friends.
The advisor information management module 363 is used to view information for an added advisor.
Example 7:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 1 to 6, further, the incentive mechanism module 37 includes a plan execution evaluation module 371, an incentive mechanism setting module 372, an incentive mechanism execution module 33, and an incentive mechanism execution recording module 374.
The plan execution evaluation module 371 is used for evaluating the taking condition according to the taking condition recording module 343;
the incentive mechanism setting module 372 is used for setting an incentive mechanism rule model by a user or an advisor, and comprises an integral value setting unit, an execution mechanism time setting unit and an execution mechanism times setting unit.
The integral value setting unit, the execution mechanism time setting unit and the execution mechanism times setting unit are respectively used for setting the excitation integral value, the execution mechanism time and the execution mechanism times.
The incentive mechanism execution module 373 is configured to execute a corresponding incentive mechanism according to the evaluation result of the plan execution evaluation module 371 and the mechanism rule set by the incentive mechanism setting module 372, and includes an integral calculation module 3731 and an incentive information pushing module 3732.
The point calculation module 3731 is configured to perform rewards, deductions and calculation of points according to the evaluation result.
The motivation information pushing module 3732 is configured to push motivation information to a user according to the data of the plan execution evaluation module 371, where the motivation information pushing includes positive and negative information, and the pushing manner includes but is not limited to popup pushing and short message pushing;
the incentive mechanism execution record module 374 is configured to store incentive mechanism execution records.
Example 8:
an intelligent medicine taking management system, the technical content of which is as in any one of embodiments 1-7, further, medicine taking conditions of users are divided into three main categories: taking medicine on time, taking medicine not on time and taking medicine more, wherein taking medicine on time is that a user strictly executes a formulated medicine taking plan, taking medicine not on time has two conditions of taking medicine without taking medicine and supplementing medicine, and taking medicine more is that the user increases medicine taking dosage; according to the three categories, the integration is added every day when taking medicine on time, the integration is not subtracted when taking medicine on time, and the addition and subtraction are not carried out when taking medicine on time. The specific values of the reward and punishment points can be set at will. The executing of the points can be that the incentive mechanism setting module sets the system to automatically execute rewards and punishments, or manually execute the rewards and punishments by the advisor side.
Example 9:
an intelligent medicine administration management system, the technical content of which is as in any one of embodiments 1-8, further, the advisor side or the user side may set rules of an incentive mechanism, such as: setting each time (generally taking 1-5 times a day) to take medicine on time by adding 10 minutes, subtracting 5 minutes each time when taking medicine not on time, setting the execution time to be 15 minutes after each time of taking medicine (such as setting 8:00 for the first time) (8:15), automatically judging whether a user takes medicine or not by the system (the system is designed to record in the system manually when the user takes medicine), wherein the execution times can be executed according to the daily medicine taking times, and also can be executed once a day.
Example 10:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 1-9, further wherein the information stored in the basic information module 381 includes one or more of gender, age, occupation, family genetic history, history of illness, and allergy history of the user.
The information stored in the physiological parameter information module 382 includes one or more of body temperature information, blood pressure information, blood glucose information, BMI, heart rate information, and blood oxygen saturation information.
The information stored in the behavior information module 383 includes one or more of recent ingestion information, exercise information, sleep information, smoking behavior information, drinking information, sexual behavior information of the user.
Example 11:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 1-10, further, the advisor side 4 further includes a professional certification module 42, a medication schedule making module 341, and a guidance evaluation module 43.
The job certification module 42 is used for consultant registration and certification of the job;
the medication schedule making module 341 is configured to make a personalized medication schedule for a user, and transmit the personalized medication schedule to the user side.
The guiding and evaluating module 43 is used for inputting guiding and evaluating results of the user's taking action and transmitting the results to the user side.
Example 12:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 1-11, further, the job certification module 42 includes a job selection module 421, a job ranking module 422, a duration of practise module 423, an academic certificate module 424, and a qualification certificate module 425.
The job selection module 421, job level module 422, practitioner duration module 423, student certificate module 424, and qualification certificate module 425 are used to record the consultant's occupation, job level, practitioner duration, student certificate, qualification certificate, respectively.
Example 13:
an intelligent medication administration system, the technical content of which is the same as that of any one of embodiments 1 to 12, further, the guidance evaluation module 43 includes an evaluation record module 431 and an evaluation report generation module 432.
The evaluation record module 431 is used for inputting the guiding evaluation result of the drug taking behavior of the user.
The evaluation report generating module 432 generates an evaluation report according to the guiding evaluation result of the user taking behavior, and transmits the evaluation report to the user side.
Example 14:
an intelligent medicine administration management system, the technical content of which is the same as any one of embodiments 1 to 13, further, the disease management module 32 includes a disease inquiry module 321, a personal disease library module 322, and a disease adding module 323.
The disease query module 321 comprises a disease classification query module 3211, a manual search query module 3212, a personal disease library query module 3213 and a disease recommendation module 3214;
the disease classification inquiry module 3211 is configured to classify and rapidly inquire about a disease according to disease data of the disease library module 211, and includes a system classification unit, an organ classification unit, a department classification unit, an age classification unit, and a gender classification unit;
the manual search query module 3212 is used for manual query of diseases by users or consultants;
the personal disease library query module 3213 is used to save the diseases that the user had.
The disease recommendation module 3214 is configured to intelligently recommend possible diseases to a user, and the diseases comprise a personal information record acquisition unit, an environment information acquisition unit and a disease matching unit, where the environment information acquisition unit acquires the area and weather information.
The personal disease library module 322 is used for storing disease information of the user, including a disease information management module 3221.
The disease information management module 3221 is used for a user to perform an add-delete-check-change operation on disease information.
The disease adding module 323 is configured to add disease information.
Example 15:
an intelligent medicine administration management system, the technical content of which is the same as that of any one of embodiments 1 to 14, further, the medicine management module 33 includes a medicine inquiry module 331, a personal medicine library module 332, a medicine adding module 333 and a medicine buying recording module 334.
The medicine query module 331 includes a medicine recommendation module 3311, a medicine classification query module 3312, a manual search query module 3212, a personal medicine library query module 3313, and a scan code query module 3314.
The medicine recommendation module 3311 performs automatic matching recommendation on the medicine in the database 21 according to the diseases added by the disease adding module 323.
The medicine recommendation module 3311 includes a disease information acquisition unit and a medicine matching unit.
The medicine classification query module 3312 is configured to rapidly query medicines according to the medicine data in the medicine library module 213, and includes a brand classification unit, a dosage form classification unit, an age classification unit, and a gender classification unit;
The manual search query module 3212 is used for manually inputting medicine name query by a user;
the personal medicine library query module 3313 is used for the user to query in the medicines added;
the code scanning inquiry module 3314 is used for the user to scan the bar code on the medicine box to directly identify and inquire the medicine;
the disease information acquisition unit is configured to acquire the disease added by the disease adding module 323.
The drug matching unit is used for automatically matching and recommending drugs in the database 21.
The personal drug library module 332 is used for storing drug information taken by the user.
The medicine adding module 333 is used for adding medicine.
The buying medicine recording module 334 is used for recording medicine information purchased by a user.
Example 16:
an intelligent medication administration system has the technical content as in any one of embodiments 1 to 15, and further, the medication execution module 34 includes a medication plan making module 341, a medication plan execution module 342, and a medication condition recording module 343.
The medication schedule making module 341 includes a medicine information viewing module 3411, a medication status display module 3412, and a medication schedule setting module 3413.
The medicine information viewing module 3411 is configured to display medicine information.
The medication status display module 3412 includes a medication on-the-fly unit, a completion planning unit, and an accident suspension unit.
The on-taking unit, the completion planning unit and the accident suspension unit record the user taking record, the taking plan completion condition and the taking suspension condition respectively.
The medicine taking plan setting module 3413 is configured to set specific daily medicine taking parameters, including a medicine taking time setting unit, a medicine taking frequency setting unit, a medicine total amount recording unit, a reminding time setting unit, and a medicine purchasing reminding setting unit.
The medication plan execution module 342 is configured to execute a plan after a user makes a medication plan, and includes a medication reminding module 3421, an incentive information pushing module 3732, a non-planned oral medication selection module 3422, and an actual medication time recording module 3423.
The medicine taking reminding module 3421 is used for reminding a user to take medicine.
The motivation information pushing module 3732 is configured to compare a result of a difference between a user-formulated taking time and an actual taking time with a preset value, and push different motivation information.
The unintended oral selection module 3422 includes a multiple-service unit and a complementary-service unit.
The multi-taking unit is used for recording the situation of taking more medicines for users.
The supplementary service unit is used for recording the supplementary service condition of the user on the dew medicine.
The actual taking time recording module 3423 is used for recording the actual taking time of the user.
The medication intake condition recording module 343 is configured to record the medication intake condition of the user.
Example 17:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 1-16, further, the medication schedule making module 341 further includes an identity security verification module 3414.
The authentication module 3414 is configured to perform authentication twice when the user side or the advisor side enters the medication planning module 341. The identity secondary verification comprises one of a password authentication unit, a fingerprint authentication unit and a face authentication unit.
Example 18:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 1 to 17, further, the medication schedule making module 341 further includes a prescription uploading identifying module 3415, a schedule prescription comparison analyzing module 3416, and a warning module 3417.
The prescription uploading identification module 3415 is used for identifying and extracting feature points from the captured prescription information of the medicine by using a related identification model algorithm after the user inputs and uploads the prescription.
The feature points include basic information of one or more medicines of medicine chemical name, prescribing hospital, prescribing doctor dosage form, dosage, specification, usage, and are transmitted to the plan prescription contrast module 3416 in the form of normalized text and/or digital content.
The plan prescription comparison analysis module 3416 is configured to compare and analyze parameters in the medication plan setting module 3413 and the prescription uploading identification module 3415, and send a warning signal to the warning module 3417 when the comparison matching result is higher than a preset value.
The warning module 3417 sends out an alarm after receiving the warning signal.
Example 19:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 1-18, further, the data transmission module 24 further includes an interface module 241, the interface module 241 is configured to obtain personal prescription data in a hospital system, and transmit the personal prescription data to a prescription upload identification module 3415;
example 20:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 1-19, further wherein the interface module 241 is further configured to provide an open interface to a specific unit for obtaining medication record data of a user in the system.
Example 21:
an intelligent medication administration system having the same technical content as in any one of embodiments 1-20, further wherein the analysis module 252 includes a disease recommendation analysis module 2521, a drug recommendation analysis module 2522, and an advisor recommendation analysis module 2523.
The disease recommendation analysis module 2521 includes a standard vector establishing unit, a real-time data vector establishing unit, a vector comparison unit, and a weight calculating unit.
The standard vector establishing unit establishes standard vectors according to the keywords in the disease library module 212 and symptom library module 213And transmitted to the vector contrast unit.
Wherein the method comprises the steps ofRepresenting symptom keywords entered by the user and corresponding data in symptom library module 213. />Representing data corresponding to keywords in the personal information record module 36 in the disease library module 212 and the symptom library module 213.b n 、p n 、a n The data corresponding to the keywords in the basic information module 361, the physiological parameter information module 362, and the behavior information module 363 in the disease library module 212 and the symptom library module 213 are respectively represented. Geographical climate information vector->r n 、w n Data corresponding to keywords in the region and weather information are represented in the disease library module 212 and the symptom library module 213, respectively.
The real timeThe data vector establishing unit establishes a vector according to the real-time data in the personal information record acquiring unit and the environment information acquiring unit in the t timeAnd transmitted to the vector contrast unit. />Real-time data in the personal information recording and acquiring unit; />Real-time data in the environment information acquisition unit; />Is data related to a disease, +.>Is data related to personal basic information, physiological parameter information, behavioral information; / >Is data related to the region and weather information.
The vector comparison unit is used for receiving the data of the standard vector establishing unit and the real-time data vector establishing unit, and vector quantityAnd->Take intersection set, recorded as (g) 1 ,g 2 ,g 3 ,...g m ) And transmitted to the weight calculation unit. m is vector->And->Number of elements of the intersection;
the weight calculation unit calculates a scoreAnd transmitted to the ranking module 253./>Representing a preset weight value for each datum. n=1, 2, …, m.
The medicine recommendation analysis module 2522 includes a keyword extraction unit, a comprehensive calculation unit, a recommendation index calculation unit, and a similarity calculation unit.
The keyword extraction unit is configured to obtain disease data in the disease adding module 323, extract disease keywords in the drug library module 214, and transmit the extracted disease keywords to the comprehensive calculation unit.
The comprehensive calculation unit is used for carrying out comprehensive weight calculation on the extracted keyword i, and the calculation formula is as followsWherein W is TP-IDF (i) TP-IDF weight value, W of key word p (i) The weight value is set according to the keywords and is transmitted to a recommendation index calculating unit. W (W) weight (i) Is the comprehensive weight;
the recommendation index calculating unit is used for calculating a recommendation index Score of the medicine according to the comprehensive weight of the keywords, and the recommendation index Score is marked as score=d 1 ·W weight (i 1 )+d 2 ·W weight (i 2 )+d 3 ·W weight (i 3 )+...+d m ·W weight (i m )。(d 1 ,d 2 ,d 3 ,...d m ) Is a set of drug vectors. (W) weight (i 1 ),W weight (i 2 ),W weight (i 3 ),...W weight (i m ) A weight set corresponding to the drug vector set).
The similarity calculation unit is used for calculating the similarity of the medicines and rootThe top k drugs are selected in descending order according to the values of the recommendation index and the similarity, and are transmitted to the sorting module 253. Wherein, the medicine similarityWherein A and B are given different drug sets. When A, B is empty, J (a, B) takes a value of 1 and the medicines with higher recommendation index and similarity index are transferred to the sorting module 253.
Example 22:
an intelligent medication administration system, the technical content of which is the same as in any one of embodiments 1-21, further wherein the advisor adding module 351 includes an advisor query module 3511 and an advisor recommendation module 3512.
The advisor recommendation module 3512 is configured to recommend an optimal advisor to a user according to diseases and advisor information added by the user, and includes an advisor type selection unit, an advisor information acquisition unit, and a recommendation index generation unit.
The result matrix B of the advisor type selection unit i ＝[B 1 ,B 2 ]Wherein B is 1 Representing doctor category, B 2 Representing a non-doctor class.
The advisor information acquisition is used to acquire information from the professional certification module 43, including a set of job title levels C i ＝[C 1 ,C 2 ,C 3 ,...,C n ]Time duration of operation matrix D i ＝[D 1 ]Set of school certificates E i ＝[E 1 ,E 2 ,E 3 ,...,E n ]Set of qualification certificates F i ＝[F 1 ,F 2 ,F 3 ,...,F n ]。F n3 Representing an nth 3 rd qualification certificate; e (E) n2 Representing an nth 2 academic certificate; c (C) n1 Represents the n1 st job title level; d (D) 1 Representing a duration of a practitioner;
the recommendation index unit is used for generating a recommendation index according to the received data, and transmitting and displaying the recommendation index to the user side in descending order.
Example 23:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 1 to 22, further, the step of generating a recommendation index by the recommendation index unit according to the received data includes:
s1, the advisor recommendation module 3512 receives information from the advisor type selection unit, the job ranking module, the duration of practise module, the student certificate module, and the qualification certificate module.
S2, acquiring data in the advisor type selection unit.
S3, if B i ＝B 1 Then generate a recommendation index Wherein C, E, F respectively represents the number, C ", D of elements in the job title level set, the academic certificate set, the qualification certificate set 1 ", E", f "are respectively expressed as the number of reference title levels, reference time duration, the number of reference academic certificates, the number of reference qualification certificates,">ω C 、/>ω E 、ω F Weighting factors respectively represented as a preset advisor type selection unit, a job ranking module (432), a duration of practise module (433), an academic certificate module (434), and a qualification certificate module (435);
If B i ≠B 1 Then generate a recommendation index Wherein omega A 、/>Expressed as preset relatives and friends and concernsAnd a weighting factor of the question type selection unit.
Example 24:
an intelligent medicine taking management system comprises an intelligent terminal and a cloud platform; the intelligent terminal comprises a user side, wherein the user side comprises a login and registration module, a disease management module, a medicine taking execution module and an authorization module.
The login and registration module is used for registering and verifying the identity of the user.
The disease management module is used for a user to search the name of the disease, add the disease and save the information of the suffering disease, and comprises a disease inquiry module, a personal disease library module and a disease adding module.
The medicine management module is used for automatically matching or manually searching the added medicines according to the diseases added by the disease adding module and storing the historically added medicine data, and comprises a medicine inquiry module, a personal medicine library module, a medicine adding module and a medicine buying recording module.
The medicine taking execution module is used for making and executing a medicine taking plan according to the medicine adding module and comprises a medicine taking plan making module, a medicine taking plan execution module and a medicine taking condition recording module.
Example 25:
the technical content of the intelligent medicine taking management system is the same as that of the embodiment 24, and further, the cloud platform comprises a database, a data acquisition module, a data storage module, a data transmission module and a data analysis module.
The database is realized by a web crawler technology and comprises a disease library module, a symptom library module, a medicine library module, a pharmacy library module, a hospital library module and a doctor library module.
The data acquisition module is used for acquiring all data involved in the system.
The data storage module is used for storing all data related to the system.
The data transmission module is used for information interaction between the systems.
The data analysis module comprises a retrieval screening module, an analysis module and a sequencing module.
Example 26:
the intelligent medication management system of any of embodiments 24-25 further comprising a disease query module including a classification query module, a manual search query module, a personal disease library query module, and a disease recommendation module.
The classifying and inquiring module is used for rapidly inquiring the diseases according to the classification of the diseases and comprises a system classifying unit, an organ classifying unit, a department classifying unit, an age classifying unit and a gender classifying unit.
The personal disease library inquiry module is used for storing diseases which the user suffers from.
The disease recommending module is used for intelligently recommending possible diseases to a user and comprises a personal information record acquiring unit, an environment information acquiring unit and a disease matching unit, wherein the environment information acquiring unit comprises an area and weather information.
Example 27:
an intelligent medication administration system, the technical content of which is as in any one of embodiments 24-26, further comprising a personal disease library module for storing disease information that the user had, including a disease information management module.
The disease information management module is used for a user to execute the operations of adding, deleting, checking and modifying the disease information.
Example 28:
the intelligent medicine taking management system has the technical content as in any one of embodiments 24-27, further comprising a medicine recommending module, a classifying and inquiring module, a manual searching and inquiring module, a personal medicine library inquiring module and a code scanning and inquiring module.
The medicine recommending module carries out automatic matching recommendation in a database according to the diseases added by the disease adding module, and the medicine recommending module comprises a disease information acquiring unit and a medicine matching unit.
Example 29:
the intelligent medicine taking management system has the technical content as in any one of embodiments 24-28, further, the medicine taking plan making module comprises a medicine information checking module, a medicine taking state display module, a medicine taking plan setting module and an identity security verification module; the medicine taking state display module comprises a medicine taking unit, a completion planning unit and an accident suspension unit; the medicine taking plan setting module is used for setting specific daily medicine taking parameters and comprises a medicine taking time setting unit, a medicine taking times setting unit, a medicine total amount recording unit, a reminding time setting unit and a medicine buying reminding setting unit; the identity security verification module is used for carrying out identity secondary verification when the user side or the consultant side enters the medicine taking plan making module, and the identity secondary verification comprises one of a password authentication unit, a fingerprint authentication unit and a face authentication unit.
Example 30:
the intelligent medicine taking management system has the technical content as in any one of embodiments 24-29, and further, the medicine taking plan making module further comprises a prescription uploading identification module, a plan prescription comparison analysis module and a warning module;
the prescription uploading identification module is used for identifying and extracting characteristic points from the captured medicine prescription information by using a related identification model algorithm after a user inputs and uploads the prescription, wherein the characteristic points comprise one or more kinds of basic medicine information in medicine chemical names, hospital and doctor dosage forms, doses, specifications and usage, and the basic medicine information is transmitted to the planning prescription comparison module in standardized text and/or digital content forms;
the plan prescription comparison analysis module is used for comparing and analyzing parameters in the medicine taking plan setting module and the prescription uploading identification module, and when the comparison and matching result is higher than a preset value, the plan prescription comparison analysis module is connected with the warning module to give a warning.
Example 31:
the intelligent medicine taking management system has the technical content as in any one of embodiments 24-30, further, the medicine taking plan execution module is used for a user to execute a plan after making a medicine taking plan, and comprises a medicine taking reminding module, an incentive information pushing module, a non-planned oral medicine taking selection module and an actual medicine taking time recording module.
The incentive information pushing module is used for comparing the result of the difference between the taking time and the actual taking time formulated by the user with a preset value and pushing different incentive information.
The non-planned oral medicine selection module comprises a multi-service unit and a supplementary service unit.
Example 32:
an intelligent medication administration system, the technical content of which is the same as any one of embodiments 24-31, further comprising a disease recommendation analysis module, a drug recommendation analysis module, and an advisor recommendation analysis module.
The disease recommendation analysis module) comprises a standard vector establishing unit, a real-time data vector establishing unit, a vector comparison unit and a weight calculating unit;
the standard vector establishing unit establishes standard vectors according to the keywords in the disease library module and the symptom library moduleWherein->Representing symptom keywords input by a user and corresponding data in a symptom library module; wherein->Representing data corresponding to keywords in the personal information record module in the disease library module and the symptom library module;wherein b n 、p n 、a n The system comprises a basic information module, a physiological parameter information module and a behavior information module, wherein the basic information module, the physiological parameter information module and the behavior information module respectively represent corresponding data of keywords in a disease library module and a symptom library module; Wherein r is n 、w n The data corresponding to the keywords in the region and the weather information in the disease library module and the symptom library module are respectively represented and transmitted to the vector comparison unit;
the real-time data vector establishing unit establishes a vector according to the data acquisition module acquiring the real-time data in the personal information record acquiring unit and the environment information acquiring unit in a period of time and the acquired dataAnd transmitting to a vector comparison unit;
the vector comparison unit is used for receiving the data of the standard vector establishing unit and the real-time data vector establishing unit, and vector quantityAnd->Taking intersection, let it be (g 1 ,g 2 ,g 3 ,...g m ) Then transmitted to the weight calculation unit for calculating the score +.>Wherein->The weight value of each preset data is represented and transmitted to the sequencing module;
the medicine recommendation analysis module comprises a keyword extraction unit, a comprehensive calculation unit, a recommendation index calculation unit and a similarity calculation unit;
the keyword extraction unit is used for acquiring disease data in the disease adding module, extracting disease keywords in the drug library module and transmitting the disease keywords to the comprehensive calculation unit;
the comprehensive calculation unit is used for carrying out comprehensive weight calculation on the extracted keyword i, and the calculation formula is as follows Wherein W is TP-IDF (i) TP-IDF weight value, W of key word p (i) The weight value is set according to the keywords and is transmitted to a recommendation index calculating unit;
the recommendation index calculation unit is used for calculating the recommendation index of the medicine according to the comprehensive weight of the keywords, and the hypothesis vector set (d 1 ,d 2 ,d 3 ,...d m ) Corresponding weight sets (W weight (i 1 ),W weight (i 2 ),W weight (i 3 ),...W weight (i m ) A calculation formula score=d) 1 ·W weight (i 1 )+d 2 ·W weight (i 2 )+d 3 ·W weight (i 3 )+...+d m ·W weight (i m )；
The similarity calculation unit is used for calculating the similarity of the medicines, and the calculation formula is as follows Wherein A, B is given set, and when A, B set is empty set, J (A, B) takes value 1, and transmits medicines with higher recommendation index and similarity index to the sorting module.
The working principle of the scheme is as follows: the intelligent terminal only comprises a user side, the user side and the cloud platform are connected with each other, diseases are added through a manual inquiry or disease recommendation module of a user, the disease recommendation module takes acquired user personal basic information and environmental information as a disease recommendation basis and transmits the disease recommendation basis to the data cloud platform, and a data analysis module in the data cloud platform analyzes and sorts the diseases and transmits the disease recommendation basis back to the user side; the medicine recommendation module is used for matching and recommending according to the diseases added by the user as medicine bases, transmitting the medicine recommendation module to the data cloud platform for similarity and comprehensive weight analysis, sequencing the medicine recommendation module, and transmitting the medicine recommendation module back to the user side; through the medicine taking execution module, the user adds the plan and executes the plan, the consultant side checks the medicine taking execution condition of the user and gives guidance and evaluation, and the user can also directly receive the plan formulated by the consultant side and execute the plan. The scheme realizes ordered and specialized management of medicine taking behaviors, and can practically help users to stop the situations of wrong medicine taking, medicine missing and medicine disorder.
The beneficial effect of this scheme lies in: first, the disease recommendation module obtains information in more various ways, but traditionally takes personal basic information as a basis, and also specifically includes environmental information factors, including obtaining one or more of longitude and latitude information, altitude information, topography information and geological information, and one or more of season information, temperature information, precipitation information and humidity information. The conventional personal basic information often comprises basic information, physiological parameter information and a behavior information module, the basic information and the physiological parameter information of a person basically do not change too much for some diseases, and the behavior information is related to the living habit of the person and basically does not change in a short time, so that the disease suffered by the person is simply analyzed from the personal basic information and lacks reliability. Therefore, the scheme adds environmental information factors as recommendation bases, and makes more accurate recommendation by combining the region where the user is and the environmental change, so as to form more complete recommendation data.
The medicine recommendation takes the diseases added by the user as a primary recommendation basis; the recommendation relevance of the medicines is stronger, the recommendation data is more accurate and more visual, and the user can conveniently and quickly find the related medicines. Traditional online medicine purchase is mostly recommended according to the sales volume, store heat and good score of medicines, and even though the traditional recommendation scheme generally classifies numerous medicines, the traditional online medicine purchase is more favorable for a database due to the fact that related medicine recommendation information is integrated, the traditional online medicine purchase does not have accurate recommendation effect, and real and effective medicine recommendation assistance cannot be provided for users. For some users, only symptoms are usually clear when purchasing the medicine, and the medicine is vague to what kind of diseases are suffered from, but the medicine purchasing method on the market does not recommend the diseases, so that the user easily purchases the wrong medicine. The medicine recommendation system of the scheme discovers the actual demands of users and the pain points of the medicines, can specially help the users to buy the medicines after knowing the diseases, and further meets the demands of the users on accurate medicine taking.
Example 33:
an intelligent medicine taking management system comprises an intelligent terminal and a cloud platform; the intelligent terminal comprises a user end and a consultant end, wherein the consultant end comprises a login and registration module and a patient information management module; the patient information management module is used for displaying and managing information of patients and comprises a patient personal information management module and a patient administration record information management module.
Example 34:
the intelligent medicine taking management system comprises a consultant management module, an incentive mechanism module and a personal information recording module.
The advisor management module is used for users to add advisors or view the information of the added advisors, and comprises an advisor adding module, a relationship binding module and an advisor information management module.
The incentive mechanism module is used for executing rewards and punishments of points or pushing positive and negative incentive information according to the medicine taking condition recording module and comprises a plan execution evaluation module, an incentive mechanism setting module, an incentive mechanism executing module and an incentive mechanism executing recording module.
The personal information recording module comprises a basic information module, a physiological parameter information module and a behavior information module.
The consultant also comprises a professional authentication module, a planning module and a guidance evaluation module.
The job certification module is used for registering and certifying the job by the consultant and comprises a job selection module, a job title level module, a duration module, an academic certificate module and a qualification certificate module.
The planning module is used for planning personalized medicine taking plan for the user and transmitting the personalized medicine taking plan to the user side.
The guiding evaluation module is used for inputting guiding evaluation results of the taking behaviors of the patient and transmitting the guiding evaluation results to the user side, and comprises an evaluation recording module and an evaluation report generating module.
Example 35:
an intelligent medication administration system, the technical content of which is the same as embodiment 34, further comprising an advisor add module including an advisor query module and an advisor recommendation module.
The consultant recommending module is used for recommending an optimal consultant to the user according to the diseases added by the user and the information of the consultant, and comprises a consultant type selecting unit, a consultant information acquiring unit and a recommendation index generating unit; the result matrix B of the advisor type selection unit i ＝[B 1 ,B 2 ]Wherein B is 1 Representing doctor category, B 2 Representing a non-doctor class; the advisor information acquisition is used to acquire information from a professional certification module (43), wherein a job title level module (432) gathers C i ＝[C 1 ,C 2 ,C 3 ,...,C n ]The method comprises the steps of carrying out a first treatment on the surface of the The duration of practise module (433) matrix D i ＝[D 1 ]The method comprises the steps of carrying out a first treatment on the surface of the The set of academic certificate modules (434) E i ＝[E 1 ,E 2 ,E 3 ,...,E n ]The method comprises the steps of carrying out a first treatment on the surface of the Set of qualification certificate modules (435) F i ＝[F 1 ,F 2 ,F 3 ,...,F n ]。
The recommendation index unit is used for generating a recommendation index according to the received data, and transmitting and displaying the recommendation index to the user side in descending order; the step of generating the recommendation index by the recommendation index unit according to the received data comprises the following steps:
s1, the consultant recommending module receives information in a consultant type selecting unit, a job title level module, a time duration module, an academic certificate module and a qualification certificate module.
S2, acquiring data in the advisor type selection unit.
S3, if B i ＝B 1 Then generate a recommendation index Wherein C, E, F respectively represents the number, C ", D of elements in the job title level set, the academic certificate set, the qualification certificate set 1 ", E", F "are respectively expressed as reference title level number, reference practice duration, reference academic certificate number, reference qualification certificate numberCount (n)/(l)>ω C 、/>ω E 、ω F The weighting factors are respectively expressed as a preset advisor type selection unit, a job title level module, a duration module, an academic certificate module and a qualification certificate module;
if B i ≠B 1 Then generate a recommendation index Wherein omega A 、/>The weighting factors expressed as preset friendship and advisor type selection units.
Example 36:
the intelligent medicine taking management system has the technical content as in any one of embodiments 34-35, further, the relationship binding module is used for binding the relationship between the user and the consultant, and comprises a doctor-patient relationship unit and a relatives-friends relationship unit; the friendship unit comprises friendship and friends, and the friendship set A i ＝[A 1 ,A 2 ]。
Example 37:
an intelligent medicine administration management system has the technical content as in any one of embodiments 34-36, further, the incentive mechanism setting module is used for setting an incentive mechanism rule model by a user or an advisor, and comprises an integral value setting unit, an execution mechanism time setting unit and an execution mechanism times setting unit.
Example 38:
the intelligent medicine taking management system has the technical content as in any one of embodiments 34-37, further, the incentive mechanism execution module is used for executing a corresponding incentive mechanism according to the evaluation result of the plan execution evaluation module and the mechanism rule set by the incentive mechanism setting module, and comprises an integral calculation module and an incentive information pushing module; the point calculation module is used for executing rewards, deductions and calculation of points according to the evaluation result.
Example 39:
an intelligent medication administration system, the technical content of which is any one of embodiments 34-38, further wherein the basic information module includes one or more of a user's gender, age, occupation, family genetic history, historical disease, allergy history;
The physiological parameter information module comprises one or more of body temperature information, blood pressure information, blood sugar information, BMI, heart rate information and blood oxygen saturation information;
the behavior information module comprises one or more of recent ingestion information, movement information, sleep information, smoking behavior information, drinking information and sexual behavior information of a user.
The working principle of the scheme has the advantages that: the intelligent terminal comprises a user end and a consultant end. Besides the advantages of the user side and the cloud platform system, the consultant side can check the medicine taking execution condition of the patient through the patient information management module and give assessment guidance advice in time, planning operation can be carried out for the chronic disease patient consultant side, the problem that a medicine taking plan cannot be made when the chronic disease patient is not allowed under the condition of the consultant side is considered, professional medicine advice can be provided for the patient through the consultant side, the supervision effect can be achieved, and great help is provided for the family doctor to manage the medicine taking problem of the chronic disease.
The beneficial effect of this scheme lies in: firstly, the consultant recommending module accurately recommends the consultants according to diseases suffered by the user and professional authentication conditions of the consultants; the setting has more accurate treatment effect on the diseases suffered by the user, and the consultant can play roles in supervising the taking of medicines, guiding the taking of medicines and evaluating the taking of medicines, and can be a medical care personnel or a relatives and friends. The conventional consultant adding mode is adopted by a user, and the adding mode is more suitable for the user to adopt an off-line medicine purchasing mode, and the on-line medicine purchasing mode cannot contact and add a professional consultant, so that the traditional mode does not enable the consultant to really play a role, and medical resources are wasted to a certain extent. According to the consultant recommendation module, the consultants can be recommended accurately according to the requirements of the user, and the requirements of the user on accurate medicine taking are met.
Secondly, taking medicine as a relatively non-positive execution event, the excitation mechanism module can excite the enthusiasm of taking medicine, especially mutual excitation of relatives and friends, the excitation mechanism of the scheme has point rewards and positive feedback information pushing rewards, the user can automatically issue rewards according to the execution condition when executing the medicine taking plan, the user can obtain feedback of the executing the medicine taking plan at the first time, the development of on-time medicine taking habit of the user is facilitated, and the medicine taking behavior is not regarded as painful behavior any more.
Example 40:
an intelligent medicine taking management system comprises an intelligent terminal 1 and a cloud platform 2; the intelligent terminal 1 comprises a user end 3 and a consultant end 4 respectively, and the intelligent terminal 1, the user end 3, the intelligent terminal 1 and the consultant end 4 are connected with the cloud platform respectively.
The working principle of the scheme has the advantages that: the intelligent terminal comprises a user terminal and a consultant terminal respectively and is connected with the cloud platform respectively, the user terminal and the consultant terminal are integrated onto the two intelligent terminals respectively to form two independent systems, so that the functions can be ensured to be in a proper range, the experience of the user is improved, and the functions are more targeted.
Example 41:
an intelligent medicine taking management system comprises an intelligent terminal 1 and a cloud platform 2; the intelligent terminal 1 comprises an integrated module 5, wherein the integrated module 5 comprises a user end 3, a consultant end 4 and a switching module 6, and the user end 3 and the consultant end 4 realize quick switching at two ends through the switching module 6.
The working principle of the scheme has the advantages that: the integrated module in the intelligent terminal comprises a switching module, the user terminal and the advisor terminal are integrated in an installation package, and the user terminal and the advisor terminal are rapidly switched through the switching module, so that a user can install a system to experience the functions of two ports, and the user is prevented from downloading the system for many times.
Claims (10)
1. An intelligent medicine taking management system is characterized in that: comprises an intelligent terminal (1) and a cloud platform (2);
the intelligent terminal (1) comprises a user side (3);
the user terminal (3) comprises a login and registration module (31), a disease management module (32), a medicine management module (33), a medicine taking execution module (34) and an authorization module (35).
The login and registration module (31) is used for registering and verifying the identity of a user;
the disease management module (32) is used for a user to search the name of the disease, add the disease and save the information of the suffering disease;
The medicine management module (33) stores a personal medicine database, and the personal medicine database is used for storing medicine data added in a history mode;
according to the diseases added by the disease management module (32), automatically matching the medicines corresponding to the diseases, adding the corresponding medicines to a personal medicine database, or manually searching by a user to add the corresponding medicines to the personal medicine database;
the medicine taking execution module (34) makes and executes a medicine taking reminding plan according to the personal medicine data in the medicine management module (33);
when the intelligent medicine taking management system needs the user to provide privacy information, the authorization module (35) acquires the personal privacy information corresponding to the user;
the cloud platform (2) comprises a database (21), a data acquisition module (22), a data storage module (23), a data transmission module (24) and a data analysis module (25);
the database (21) comprises a disease library module (211), a symptom library module (212), a medicine library module (213), a pharmacy library module (214), a hospital library module (215) and a doctor library module (216), which are respectively used for storing a plurality of pieces of disease information, symptoms corresponding to each disease, a plurality of pieces of medicine information, a plurality of pieces of pharmacy information, a plurality of pieces of hospital information and a plurality of pieces of doctor information;
The data acquisition module (22) is used for acquiring all data related in the database (21) and storing the data into the database (21);
the data storage module (23) is used for storing all data uploaded by the intelligent terminal;
the data transmission module (24) is used for realizing information interaction between the intelligent terminal (1) and the cloud platform (2) or information interaction between the cloud platform (2) and the outside;
the data analysis module (25) comprises a retrieval screening module (251), an intelligent analysis engine module (252) and a sequencing module (253);
the retrieval screening module (251) is used for retrieving data in the database (21) and transmitting the data to the intelligent analysis engine module (252);
the intelligent analysis engine module (252) analyzes the data uploaded by the intelligent terminal (1) and the data in the database (21), determines diseases and disease weights corresponding to user symptoms if intervention is performed, and a plurality of recommended medicines and medicine recommendation indexes and medicine similarity corresponding to each disease, and transmits the medicines and the weights to the sequencing module (253);
the sequencing module (253) performs descending order arrangement on the pre-suffering diseases according to the disease weights, performs descending order arrangement on the recommended medicines according to the medicine recommendation indexes and the medicine similarity, and transmits the arranged pre-suffering diseases and the recommended medicines to the intelligent terminal (1).
2. An intelligent medication management system according to claim 1, characterized in that the intelligent terminal (1) further comprises an advisor side (4);
the user side (3) performs data interaction with the cloud platform (2);
and the advisor side (4) performs data interaction with the cloud platform (2).
The advisor side (4) comprises a login and registration module (31) and a user information management module (41);
-said login-registration module (31) for registering and verifying a advisor identity;
the user information management module (41) is used for displaying and managing information of a user, and comprises a user personal information management module (411) and a user medicine taking record information management module (412);
the user personal information management module (411) is used for displaying and managing user personal information from the user side (3);
the user medicine taking record information management module (412) is used for displaying and managing the user medicine taking record information from the user side (3).
3. The intelligent medication management system according to claim 2, characterized in that the intelligent terminal (1) further comprises a switching module (6);
the user end (3), the advisor end (4) and the switching module (6) are integrated in the integration module (5);
the user end (3) and the advisor end (4) are switched through a switching module (6).
4. The intelligent medication management system as recited in claim 1, wherein the client (3) further comprises an advisor management module (36), an incentive mechanism module (37) and a personal information record module (38);
the advisor management module (36) is used for users to add advisors or manage the information of the added advisors;
the advisor management module (36) comprises an advisor adding module (361), a relationship binding module (362) and an advisor information management module (363);
the advisor adding module (361) is used for adding the advisor;
the relationship binding module (362) is used for binding the relationship between the user and the consultant; the relationship comprises doctor-patient relationship and relatives-friends relationship; the relatives and friends comprise relatives and friends;
the advisor information management module (363) is configured to view information of an added advisor;
the incentive mechanism module (37) executes rewards and punishments of points and/or pushes of positive and negative incentive information according to the information of the medicine taking condition recording module (343);
the incentive mechanism module (37) comprises a plan execution evaluation module (371), an incentive mechanism setting module (372), an incentive mechanism execution module (373) and an incentive mechanism execution recording module (374);
The plan execution evaluation module (371) is used for evaluating the taking condition according to the taking condition recording module (343);
the incentive mechanism setting module (372) is used for setting an incentive mechanism rule model by a user or an advisor and comprises an integral value setting unit, an execution mechanism time setting unit and an execution mechanism times setting unit;
the integral value setting unit, the execution mechanism time setting unit and the execution mechanism times setting unit are respectively used for setting an excitation integral value, an execution mechanism time and an execution mechanism times;
the incentive mechanism executing module (373) is used for executing a corresponding incentive mechanism according to the evaluation result of the plan executing evaluation module (371) and the mechanism rule set by the incentive mechanism setting module (372), and comprises an integral calculating module (3731) and an incentive information pushing module (3732);
the point calculation module (3731) is used for executing rewards, deductions and calculation of points according to the evaluation result.
The incentive information pushing module (3732) is used for pushing incentive information to a user according to the data of the plan execution evaluation module (371), wherein the incentive information pushing comprises positive and negative information, and the pushing modes comprise, but are not limited to, popup pushing and short message pushing;
The incentive mechanism execution record module (364) is used for storing an incentive mechanism execution record;
the personal information recording module (38) comprises a basic information module (381), a physiological parameter information module (382) and a behavior information module (383);
the information stored in the basic information module (381) includes one or more of user gender, age, occupation, family genetic history, historical disease, allergy history;
the information stored in the physiological parameter information module (382) comprises one or more of body temperature information, blood pressure information, blood glucose information, BMI, heart rate information and blood oxygen saturation information;
the information stored in the behavior information module (383) comprises one or more of recent ingestion information, movement information, sleep information, smoking behavior information, drinking information and sexual behavior information of the user.
5. The intelligent medication management system of claim 2, wherein the advisor side (4) further comprises a professional certification module (42), a medication planning module (341), and a coaching assessment module (43);
the job authentication module (42) is used for registering and authenticating the occupation by the consultant, and comprises an occupation selection module (421), a job title level module (422), a duration of practise module (423), an academic certificate module (424) and a qualification certificate module (425);
The job selection module (421), the job ranking module (422), the duration module (423), the learning certificate module (424) and the qualification certificate module (425) are respectively used for recording the occupation, the job ranking, the duration, the learning certificate and the qualification certificate of the consultant;
the medicine taking plan making module (341) is used for making a personalized medicine taking plan for a user and transmitting the personalized medicine taking plan to the user side (3);
the guiding and evaluating module (43) is used for inputting guiding and evaluating results of the medicine taking behaviors of the user and transmitting the guiding and evaluating results to the user side, and comprises an evaluating and recording module (431) and an evaluating report generating module (432);
the evaluation recording module (431) is used for inputting the guiding evaluation result of the medicine taking behavior of the user;
the evaluation report generating module (432) generates an evaluation report according to the guiding evaluation result of the medicine taking behavior of the user and transmits the evaluation report to the user side (3).
6. The intelligent medication management system of claim 1, wherein the disease management module (32) comprises a disease query module (321), a personal disease library module (322), a disease add module (323);
the disease query module (321) comprises a disease classification query module (3211), a manual search query module (3212), a personal disease library query module (3213) and a disease recommendation module (3214);
The disease classification inquiry module (3211) is used for classifying and rapidly inquiring diseases according to the disease data of the disease library module (211), and comprises a system classification unit, an organ classification unit, a department classification unit, an age classification unit and a gender classification unit;
the manual search query module (3212) is used for manual query of diseases by a user or consultant;
the personal disease library inquiry module (3213) is used for storing diseases that the user suffers from;
the disease recommendation module (3214) is used for intelligently recommending possible diseases to a user, and comprises a personal information record acquisition unit, an environment information acquisition unit and a disease matching unit, wherein the environment information acquisition unit comprises an area and weather information to which the user belongs.
The personal disease library module (322) is used for storing disease information of a user, and comprises a disease information management module (3221);
the disease information management module (3221) is used for a user to perform addition, deletion, check and modification operations on disease information;
the disease adding module (323) is used for adding disease information;
the medicine management module (33) comprises a medicine inquiry module (331), a personal medicine library module (332), a medicine adding module (333) and a medicine buying recording module (334);
The medicine query module (331) comprises a medicine recommendation module (3311), a medicine classification query module (3312), a manual search query module (3212), a personal medicine library query module (3313) and a code scanning query module (3314);
the medicine recommending module (3311) automatically carries out matching recommendation on medicines in the database (21) according to the diseases added by the disease adding module (323); the medicine recommendation module (3311) includes a disease information acquisition unit and a medicine matching unit;
the medicine classification inquiry module (3312) is used for rapidly inquiring medicines according to the medicine data in the medicine library module (213), and comprises a brand classification unit, a dosage form classification unit, an age classification unit and a gender classification unit;
the manual search query module (3212) is used for manually inputting a medicine name query by a user;
the personal medicine library query module (3313) is used for a user to query in medicines which are added;
the code scanning query module (3314) is used for a user to scan the bar code on the medicine box to directly identify and query the medicine;
the disease information acquisition unit is used for acquiring the diseases added by the disease adding module (323);
the medicine matching unit is used for automatically matching and recommending medicines in the database (21);
The personal medicine library module (332) is used for storing medicine information taken by a user;
the medicine adding module (333) is used for adding medicines;
the buying medicine recording module (334) is used for recording medicine information purchased by a user.
The medicine taking execution module (34) comprises a medicine taking plan making module (341), a medicine taking plan execution module (342) and a medicine taking condition recording module (343);
the medicine taking plan making module (341) comprises a medicine information viewing module (3411), a medicine taking state display module (3412) and a medicine taking plan setting module (3413);
the medicine information viewing module (3411) is used for displaying medicine information;
the medicine taking state display module (3412) comprises a medicine taking unit, a completion planning unit and an accident suspension unit;
the on-taking unit, the completion planning unit and the accident suspension unit record the user taking record, the taking plan completion condition and the taking suspension condition respectively;
the medicine taking plan setting module (3413) is used for setting specific medicine taking parameters every day, and comprises a medicine taking time setting unit, a medicine taking times setting unit, a medicine total amount recording unit, a reminding time setting unit and a medicine buying reminding setting unit;
the medicine taking plan execution module (342) is used for a user to execute a plan after making a medicine taking plan, and comprises a medicine taking reminding module (3421), an incentive information pushing module (3732), a non-planned oral medicine selection module (3422) and an actual medicine taking time recording module (3423);
The medicine taking reminding module (3421) is used for reminding a user of taking medicine;
the incentive information pushing module (3732) is used for comparing the result of the difference between the taking time and the actual taking time formulated by the user with a preset value and pushing different incentive information;
the unintended oral drug selection module (3422) includes a multiple-administration unit and a complementary-administration unit.
The multi-taking unit is used for recording the situation of multiple taking medicines of a user;
the supplementary service unit is used for recording the supplementary service condition of the user for missed medicine taking;
the actual taking time recording module (3423) is used for recording the actual taking time of a user;
the medicine taking condition recording module (343) is used for recording the medicine taking condition of a user.
7. The intelligent medication management system of claim 6, wherein the medication schedule execution module (341) further comprises an identity security verification module (3414), the identity security verification module (3414) being configured to perform identity secondary verification when a user side or a consultant side enters the medication schedule formulation module (341); the identity secondary verification comprises one of a password authentication unit, a fingerprint authentication unit and a face authentication unit.
8. The intelligent medication management system of claim 7, wherein the medication scheduling module (341) further comprises a prescription upload identification module (3415), a scheduled prescription contrast analysis module (3416), and a warning module (3417);
The prescription uploading identification module (3415) is used for identifying and extracting characteristic points of the captured medicine prescription information by utilizing a related identification model algorithm after a user inputs and uploads the prescription;
the characteristic points comprise basic information of one or more medicines in the medicine chemical name, the prescribing hospital, the prescribing doctor dosage form, the dosage, the specification and the usage, and the basic information is transmitted to the plan prescription comparison module (3416) in the form of standardized text and/or digital content;
the plan prescription comparison analysis module (3416) is used for comparing and analyzing parameters in the medicine taking plan setting module (3413) and the prescription uploading identification module (3415), and sending a warning signal to the warning module (3417) when the comparison and matching result is higher than a preset value;
the warning module (3417) sends out an alarm after receiving the warning signal;
the data transmission module (24) further comprises an interface module (241), wherein the interface module (241) is used for acquiring personal prescription data in a hospital system and transmitting the personal prescription data to the prescription uploading identification module (3415);
the interface module (241) is also used for providing an open interface for a specific unit to acquire medicine taking record data of a user in the system.
9. The intelligent medication management system of claim 1, wherein the intelligent analysis engine module (252) comprises a disease recommendation analysis module (2521), a drug recommendation analysis module (2522), and an advisor recommendation analysis module (2523);
The disease recommendation analysis module (2521) comprises a standard vector establishment unit, a real-time data vector establishment unit, a vector comparison unit and a weight calculation unit;
the standard vector establishing unit establishes standard vectors according to the keywords in the disease library module (212) and the symptom library module (213)And transmitting to a vector comparison unit;
wherein the method comprises the steps ofData representing symptom keywords entered by a user and corresponding in a symptom library module (213); />Representation and personal information recording module36 Data corresponding to the keywords in the disease library module (212) and the symptom library module (213);b n 、p n 、a n data corresponding to keywords in the basic information module (361), the physiological parameter information module (362) and the behavior information module (363) in the disease library module (212) and the symptom library module (213) are respectively represented; geographical climate information vector->r n 、w n Data corresponding to keywords in the region and weather information in a disease library module (212) and a symptom library module (213) are respectively represented;
the real-time data vector establishing unit establishes a vector according to the real-time data in the personal information record acquiring unit and the environment information acquiring unit in the t timeAnd transmitting to a vector comparison unit; />Real-time data in the personal information recording and acquiring unit; / >Real-time data in the environment information acquisition unit;
the vector comparison unit is used for receiving the data of the standard vector establishing unit and the real-time data vector establishing unit, and vector quantityAnd->Take intersection set, recorded as (g) 1 ,g 2 ，g 3 ,...g m ) And transmitting to the weight calculation unit; m is vector->And->Number of elements of the intersection;
the weight calculation unit calculates a scoreAnd transmitted to a ranking module (253); />A preset weight value of each datum is represented; n=1, 2, m;
the medicine recommendation analysis module (2522) comprises a keyword extraction unit, a comprehensive calculation unit, a recommendation index calculation unit and a similarity calculation unit;
the keyword extraction unit is used for acquiring disease data in the disease adding module (323), extracting disease keywords in the drug library module (214), and transmitting the disease keywords to the comprehensive calculation unit;
the comprehensive calculation unit is used for carrying out comprehensive weight calculation on the extracted keyword i, and the calculation formula is as followsWherein W is TP-IDF (i) TP-IDF weight value, W of key word p (i) The weight value is set according to the keywords and is transmitted to a recommendation index calculating unit; w (W) weight (i) Is the comprehensive weight;
the recommendation index calculation unit is used for calculating the recommendation index of the medicine according to the comprehensive weight of the keywords, and the recommendation index is recorded as score=d 1 ·W weight (i 1 )+d 2 ·W weight (i 2 )+d 3 ·W weight (i 3 )+...+d m ·W weight (i m )；(d 1 ，d 2 ，d 3 ，...d m ) Is a medicine vector set;
(W weight (i 1 )，W weight (i 2 )，W weight (i 3 )，...W weight (i m ) A weight set corresponding to the medicine vector set;
the similarity calculation unit is used for calculating the similarity of the medicines, selecting the first k medicines in a descending order according to the recommended index and the numerical value of the similarity, and transmitting the medicines to the ordering module (253); wherein, the medicine similarityWherein A and B are given different drug sets; when A, B is empty, J (A, B) is 1, and the medicines with higher recommendation index and similarity index are transmitted to the sorting module (253).
10. The intelligent medication management system of claim 5 wherein said advisor addition module (351) comprises an advisor query module (3511) and an advisor recommendation module (3512);
the counselor recommendation module (3512) is used for recommending an optimal counselor to the user according to the diseases added by the user and the information of the counselor, and comprises a counselor type selection unit, a counselor information acquisition unit and a recommendation index generation unit;
the result matrix B of the advisor type selection unit i ＝[B 1 ,B 2 ]Wherein B is 1 Representing doctor category, B 2 Representing a non-doctor class;
the advisor information acquisition is used to acquire information from a professional certification module (43), including a set of job title levels C i ＝[C 1 ,C 2 ,C 3 ,...,C n1 ]Time duration of operation matrix D i ＝[D 1 ]Set of school certificates E i ＝[E 1 ,E 2 ,E 3 ,...,E n2 ]Set of qualification certificates F i ＝[F 1 ,F 2 ,F 3 ,...,F n3 ]；F n3 Representing an nth 3 rd qualification certificate; e (E) n2 Representing an nth 2 academic certificate; c (C) n1 Represents the n1 st job title level; d (D) 1 Representing a duration of a practitioner;
the recommendation index unit is used for generating a recommendation index according to the received data, and transmitting and displaying the recommendation index to the user side in descending order;
the step of generating the recommendation index by the recommendation index unit according to the received data comprises the following steps:
s1, the consultant recommending module (3512) receives information in a consultant type selecting unit, a job title level module, a time duration module, an academic certificate module and a qualification certificate module;
s2, acquiring data in the advisor type selection unit;
s3, if B i ＝B 1 Then generate a recommendation index Wherein C, E, F respectively represents the number, C ", D of elements in the job title level set, the academic certificate set, the qualification certificate set 1 ", E", F "are respectively expressed as reference title level number, reference practice duration, reference academic certificate number, reference qualification certificate number, < >>ω C 、/>ω E 、ω F Weighting factors respectively represented as a preset advisor type selection unit, a job ranking module (432), a duration of practise module (433), an academic certificate module (434), and a qualification certificate module (435);
If B i ≠B 1 Then generate a recommendation index Wherein->The weight factor is expressed as a preset friendship.
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