CN114255869B - Medical big data cloud platform - Google Patents
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Abstract
The medical big data cloud platform comprises a database, a database and a database server, wherein the database is prestored with first login information, medical record data, disease diagnosis data and recommended content data of registered users; the input module is used for registering the input of second login information and interactive data of a user; a processor; when the processor judges that the second login information is matched with the first login information, a signal of successful login is output, disease diagnosis data and recommended content data are output through interactive data input by the registered user, the illness condition of the registered user is preliminarily diagnosed, the registered user is made to know the detailed condition of the illness, auxiliary medical service is provided for the registered user, and the registered user can conveniently see a doctor further.
Description
Technical Field
The invention relates to the field of big data medical information, in particular to a medical big data cloud platform capable of providing auxiliary treatment service.
Background
With the rapid development of internet technology and medical level, the medical field enters the era of big data, and the hospitalizing process of people gradually becomes convenient and efficient. However, in some big cities, the public resource distribution in the society is unbalanced due to the increase of population and the influx of foreign people, especially the medical resource in the big cities.
Due to the lack of relevant medical knowledge, when the physical condition of people is in a problem, the actual severity of the disease and the diagnosis and treatment range of a specific department are not known, so that slight discomfort is caused, the people need to queue and register for a long time in a fierce hospital every day, and the condition of hanging wrong departments often occurs, so that repeated registration and queuing are directly caused, time, energy and money are wasted, the time for disease treatment is delayed sometimes, and the waste of public medical resources is caused. Therefore, a medical big data cloud platform capable of providing auxiliary treatment services is needed.
Disclosure of Invention
The invention aims to provide a medical big data cloud platform capable of providing auxiliary treatment service.
The invention relates to a medical big data cloud platform, which comprises
A database in which first login information, medical record data, disease diagnosis data, and recommended content data of a registered user are prestored;
the input module is used for registering the input of second login information and interactive data of a user;
and the processor is used for judging whether the second login information is matched with the first login information, outputting a repeated login signal if the second login information is not matched with the first login information, and outputting a login success signal if the second login information is matched with the first login information.
The invention relates to a medical big data cloud platform, wherein the step that a processor can output disease diagnosis data corresponding to interactive data according to the interactive data comprises the following steps:
the database is also pre-stored with a primary interface, and the primary interface comprises primary problem data, a primary stereo model and primary position data; the database is also pre-stored with a secondary interface corresponding to the primary position data, and the secondary interface comprises secondary problem data, a secondary three-dimensional model and secondary position data;
the input module is electrically connected with the display module, and the display module is used for displaying a primary interface and a secondary interface;
the display module displays a primary interface and displays a primary three-dimensional model at a first initial visual angle;
the processor acquires first click time of the registered user on the primary three-dimensional model, judges whether the first click time is smaller than a first preset threshold value, and if yes, the processor captures primary part data of the registered user on the primary three-dimensional model, controls the display module to display a secondary interface corresponding to the primary part data, and displays the secondary three-dimensional model at a second initial view angle;
the processor acquires second click time of the registered user on the secondary three-dimensional model, judges whether the second click time is smaller than a first preset threshold value, and if yes, the processor captures at least one secondary part data of the secondary three-dimensional model clicked by the registered user and outputs disease diagnosis data corresponding to the secondary part data through the first step.
The invention relates to a medical big data cloud platform, wherein reference position data corresponding to secondary position data, at least one piece of reference disease data corresponding to the reference position data and reference description information corresponding to the reference disease data are also stored in a database;
the first step comprises:
the processor acquires a plurality of reference characteristic information in the reference description information corresponding to the reference disease data and marks the plurality of reference characteristic information as K i ；
The user inputs the contrast description information through the input module;
the processor acquires a plurality of pieces of contrast characteristic information in the contrast description information and marks the plurality of pieces of contrast characteristic information as L i ；
The processor calculates contrast characteristic information L i And reference characteristic information K i Judging whether the matching degree P is smaller than a first numerical value, and if so, outputting a signal which does not suffer from the disease; if not, judging whether the matching degree P is between a first value and a second value, and if so, outputting a signal possibly suffering from the disease; if not, a signal with a high probability of suffering from the disease is output.
The invention relates to a medical big data cloud platform, wherein a processor updates a first initial view angle of a primary stereo model and a second initial view angle of a secondary stereo model according to at least one captured secondary position data of a registered user clicking the secondary stereo model.
According to the medical big data cloud platform, when the processor judges that the second login information is matched with the first login information, the processor can call medical record data, reference disease data, disease diagnosis data and recommendation content data corresponding to a registered user.
The invention relates to a medical big data cloud platform, wherein a processor is electrically connected with an input module and a display module.
The invention relates to a medical big data cloud platform, wherein a first initial visual angle is an initial visual angle corresponding to a first-level three-dimensional model in a first-level interface when a user inquires a disease.
The invention relates to a medical big data cloud platform, wherein a second initial visual angle is an initial visual angle corresponding to a secondary stereo model in a secondary interface when a user inquires a disease.
The invention relates to a medical big data cloud platform, wherein the comparative characteristic information is description of the characteristics of a disease of a registered user.
The medical big data cloud platform is different from the prior art in that the medical big data cloud platform outputs disease diagnosis data and recommended content data through interactive data input by registered users, preliminarily diagnoses the illness condition of the registered users, enables the registered users to know the detailed condition of the illness of the registered users, and provides auxiliary treatment service for the registered users, so that the registered users can conveniently see the doctor.
The medical big data cloud platform of the invention is further explained with reference to the accompanying drawings.
Drawings
FIG. 1 is a flow diagram of a medical big data cloud platform;
FIG. 2 is a schematic of a primary interface;
FIG. 3 is a schematic diagram of a secondary interface corresponding to a hand;
fig. 4 is a schematic diagram of a first step.
Detailed Description
As shown in FIG. 1~4, referring to FIG. 1, a medical big data cloud platform of the present invention comprises
A database in which first login information, medical record data, disease diagnosis data, and recommended content data of a registered user are prestored;
the input module is used for registering the input of second login information and interactive data of a user;
and the processor is used for judging whether the second login information is matched with the first login information, outputting a repeated login signal if the second login information is not matched with the first login information, and outputting a login success signal if the second login information is matched with the first login information.
According to the invention, when the processor judges that the second login information is matched with the first login information, a signal of successful login is output, the disease diagnosis data and the recommended content data are output through the interactive data input by the registered user, and the illness condition of the registered user is preliminarily diagnosed, so that the registered user can know the detailed condition of the illness, and the auxiliary medical service is provided for the registered user, thereby facilitating the further medical treatment of the registered user.
The server comprises a database and a processor which are electrically connected with each other, and the user terminal comprises an input module and a display module which are electrically connected with each other. The registered user can provide the input module to input the second login information and the interactive data, and after the second login information and the interactive data are processed by the processor, the disease diagnosis data and the recommended content data are displayed to the registered user through the display module.
The first login information comprises an account and a password which are set by the patient, and the second login information comprises the account, the password, a randomly generated verification code and the like. When a registered user logs in, an account and a corresponding password are input in an input box, a button for acquiring a verification code appears after the password is input correctly, the randomly generated verification code sent by the system is received after the button for acquiring the verification code is clicked, and the user can log in smoothly after the verification code is input correctly for subsequent operation, for example, medical record data corresponding to the registered user can be called in a database.
According to the invention, through the setting, double verification of the password and the verification code is realized, the login security of the registered user is improved, and the account security of the registered user is ensured.
Wherein the medical record data comprises: name, sex, age, address, contact, medical history, and the like.
The input module can be information input equipment such as a mobile phone screen, a computer keyboard, a mouse and the like.
The interactive data is an action performed by the registered user through the input module, for example, by clicking different positions of a screen of a mobile phone, or clicking different positions of the screen through a computer mouse, or typing characters through a computer keyboard.
Wherein the recommended content data includes: recommended treatment departments, recommended treatment hospitals, cautionary matters and the like corresponding to the disease diagnosis data.
As a further explanation of the present invention, referring to fig. 1,2 and 3, the step of "the processor can output disease diagnosis data corresponding to the interactive data according to the interactive data" includes:
the database is also pre-stored with a primary interface, and the primary interface comprises primary problem data, a primary stereo model and primary position data; the database is also pre-stored with a secondary interface corresponding to the primary position data, and the secondary interface comprises secondary problem data, a secondary three-dimensional model and secondary position data;
the input module is electrically connected with the display module, and the display module is used for displaying a primary interface and a secondary interface;
the display module displays a primary interface and displays a primary three-dimensional model at a first initial visual angle;
the processor acquires first click time of the registered user on the primary three-dimensional model, judges whether the first click time is smaller than a first preset threshold value, and if yes, the processor captures primary part data of the registered user on the primary three-dimensional model, controls the display module to display a secondary interface corresponding to the primary part data, and displays the secondary three-dimensional model at a second initial view angle;
the processor judges whether the second click time is smaller than a first preset threshold value, if yes, the processor captures at least one second-level part data of the second-level three-dimensional model clicked by the registered user, and disease diagnosis data corresponding to the second-level part data are output through the first step.
The method comprises the steps of prompting a registered user to generate approximate uncomfortable positions by displaying question data, displaying a secondary stereo model which is displayed at a second initial view angle and selected and clicked by the registered user after the user selects and clicks primary position data corresponding to primary stereo data displayed at a first initial view angle, prompting the registered user to generate specific uncomfortable positions by displaying secondary question data, and outputting corresponding disease diagnosis data through a first step after the user selects and clicks secondary position data corresponding to the secondary stereo data. According to the method, the uncomfortable parts which the registered user wants to select are gradually enlarged by utilizing the visual angle diversity and adjustability of the three-dimensional model, and finally, selection clicking is carried out, so that the registered user can conveniently find and select the position where the registered user feels uncomfortable, and the corresponding disease diagnosis data and the recommended content data can be conveniently provided subsequently.
Referring to fig. 2, the first-level question data is a prompt for guiding a registered user to click on the position of the first-level stereo model. Ask you where it is uncomfortable, for example.
Wherein, the primary three-dimensional model is a perspective view of the whole body structure of the human body. The first-level position data is a position name corresponding to the first-level three-dimensional model. For example, the primary location data may be a name including, but not limited to, the following structure: head, neck, back, abdomen, arms, hands, legs, feet, etc., as well as internal organs such as lungs, heart, liver, stomach, intestines, etc., see fig. 2.
Wherein the registered user can control the angle of view orientation of the primary stereo model so that the registered user can find the body part that the registered user wants to click.
Wherein the first preset threshold is 0.1 to 1s, and preferably 0.2s.
If the first click time is greater than a first preset threshold, it indicates that the registered user cannot find or cannot easily find the body part that the registered user wants to click on the first-level stereo model at the current view angle, and the view angle of the first-level stereo model is being adjusted, in other words, when the click event of the registered user exceeds the first preset threshold, it indicates that the registered user drags or rotates the first-level stereo model or the second-level stereo model.
Referring to fig. 3, the second-level question data is a prompt for guiding the registered user to click the position of the second-level stereoscopic model. For example, to say specifically where the felt is uncomfortable.
Wherein the secondary stereoscopic model is a partially enlarged perspective view of the first model data corresponding to the first click position of the registered user, which can display the region information of a certain part of the body in more detail and clearly. The secondary location data is a location name corresponding to the secondary three-dimensional model, for example, the secondary three-dimensional model of a hand may be a name including but not limited to the following structure: wrist, palm, thumb, index finger, etc., see fig. 3.
Wherein the registered user can control the angle of view orientation of the secondary stereoscopic model so that the registered user can find the body part that the registered user wants to click on.
And the unit of the first click time and the unit of the second click time are both s.
For example, referring to fig. 2 and 3, after the registered user successfully logs in, the display module jumps to a first-level interface, first-level question data similar to "ask you where you are uncomfortable" is displayed at the top of the first-level interface, and a first-level stereoscopic model including a perspective view of the whole body structure of the human body and corresponding first-level position data are displayed below the first-level interface. In the selection process, if the first click time of the registered user clicking a certain position of the primary stereo model exceeds 0.2s, it is indicated that the registered user is adjusting the view angle of the primary stereo model to find a body part to be clicked, if the first click time does not exceed 0.2s, it is indicated that the registered user has clicked the primary part data of the primary stereo model, for example, the primary part data clicked by the registered user is a hand, the display module jumps to a secondary interface corresponding to the hand, secondary problem data similar to "where the registered user is uncomfortable" is displayed on the top of the secondary interface, the secondary stereo model including the hand and the corresponding secondary part data are displayed below the secondary interface, the registered user can still adjust the view angle of the secondary stereo model of the hand to find the secondary part data corresponding to the hand that the registered user wants to click, for example, the registered user clicks one secondary part data as a "wrist", and disease diagnosis data corresponding to the secondary part data "wrist" is output through the first step.
As a further explanation of the present invention, referring to fig. 1,2, 3 and 4, the database further stores therein reference position data corresponding to the secondary position data, at least one reference disease data corresponding to the reference position data, and reference description information corresponding to the reference disease data;
the first step comprises:
the processor acquires a plurality of reference characteristic information in the reference description information corresponding to the reference disease data and marks the plurality of reference characteristic information as K i ；
The user inputs the contrast description information through the input module;
the processor acquires a plurality of pieces of contrast characteristic information in the contrast description information and marks the plurality of pieces of contrast characteristic information as L i ；
The processor calculates contrast characteristic information L i And reference characteristic information K i Judging whether the matching degree P is smaller than a first numerical value, and if so, outputting a signal which does not suffer from the disease; if not, judging whether the matching degree P is between a first value and a second value, and if so, outputting a signal possibly suffering from the disease; if not, a signal with a high probability of suffering from the disease is output.
The invention obtains a plurality of reference characteristic information in the reference description information and a plurality of comparison characteristic information in the comparison description information, calculates the matching degree P of the plurality of reference characteristic information and the plurality of comparison characteristic information, and outputs different disease signals to the registered user according to the relation between the value of the matching degree P and the first value and the second value. The invention matches the disease characteristics input by the registered user with the reference disease characteristics through the method, and judges the matching degree P, thereby leading the user to know the type and the name of the disease.
Wherein the reference position data is a specific body part that the registered user is likely to feel uncomfortable. Such as nerve analgesia, joint numbness and weakness, various skin discomfort symptoms, muscle soreness, tendon pain, various nail diseases and the like.
The present invention, by the above arrangement, realizes reference position data that can be determined to be known according to a specific site of discomfort felt by the registered user's body.
Wherein the reference disease data is a disease name corresponding to the reference position data. For example, reference disease data relating to skin may include: eczema of hands, tinea manuum, pompholyx, psoriasis, etc.; the reference disease data relating to the muscle may include: hand muscle atrophy, hand muscle strain, etc.; the reference disease data relating to nerves can include: carpal tunnel syndrome and the like; reference disease data related to a joint may include: rheumatoid arthritis, gouty arthritis, osteoarthritis, and the like; the tendon-related reference disease data may include: tenosynovitis, and the like; the reference disease data relating to the nail may include: onychomycosis, and the like.
Wherein the reference characteristic information is a characteristic description of reference disease data. For example, rheumatoid arthritis is characterized by: the pain and swelling dysfunction is serious, the proximal interphalangeal joints, the metacarpophalangeal joints and the wrist joints are more frequently invaded and are distributed symmetrically, namely, the hand joints on two sides are simultaneously painful, morning stiffness is heavy, the duration is long, and the finger joints can be obviously deformed.
Wherein i =1,2.. N.
Wherein the first value is 0 to 30%, preferably 20%.
Wherein the second value is 30% to 90%, preferably 70%.
As a variation of the present invention, referring to fig. 1,2, 3, and 4, a primary lexicon and a secondary lexicon corresponding to secondary position data are further stored in the database, wherein the primary lexicon includes at least one reference disease data, and the secondary lexicon includes reference description information corresponding to the reference disease data;
the first step comprises:
the processor acquires a plurality of reference characteristic information in the reference description information corresponding to the reference disease data and marks the plurality of reference characteristic information as K i ；
The processor acquires a plurality of pieces of contrast characteristic information in the contrast description information and marks the contrast characteristic information as L i ；
The processor judges whether the comparison characteristic information is the same as the reference disease data or not, and if so, outputs a signal which is corresponding to the reference disease data and suffers from the disease; if not, the processor calculates the contrast characteristic information L i And reference characteristic information K i According to the sequence of the matching degree P from large to small, the matching degree P is compared with the reference characteristic information K i The corresponding reference disease data are arranged from top to bottom.
The invention calculates the matching degree P of the reference characteristic information and the contrast characteristic information by acquiring the reference characteristic information and the contrast characteristic information in the reference description information and the contrast description information, and matches the reference characteristic information with the reference characteristic information K according to the numerical value of the matching degree P i The corresponding reference disease data are arranged from top to bottom, so that the registered user can know that the more upper reference disease data are more consistent with the disease suffered by the registered user. By the method, the invention matches the disease characteristics input by the registered user with the reference disease characteristics, and arranges the matching degree P from large to small, thereby leading the user to know the type and name of the disease possibly belonging to the user.
Wherein the value of the matching degree P represents the contrast characteristic information L i And reference characteristic information K i The greater the numerical value of the matching degree P, the more the registered user suffers from and is referred to the reference characteristic information K i The greater the probability that the corresponding reference disease data corresponds to a disease. The registered user can judge the possibility of suffering from a certain disease through the upper and lower positions of the output reference disease data.
As a further explanation of the present invention, referring to fig. 1,2, 3, and 4, the database is pre-stored with keyword data;
the processor acquires a plurality of reference characteristic information in the reference description information corresponding to the reference disease data and marks the plurality of reference characteristic information as K i (ii) a The user inputs the contrast description information through the input module; the processor acquires a plurality of pieces of contrast characteristic information in the contrast description information and marks the plurality of pieces of contrast characteristic information as L i (ii) a The processor calculates contrast characteristic information L i And reference characteristic information K i The matching degree P "of (a) is:
the processor screens out part nouns and sensory adjectives which are the same as the keyword data in the reference description information corresponding to the reference disease data to generate a plurality of reference characteristic information, and calculates the total number of the reference characteristic information to be m, wherein the reference characteristic information is marked as K 1 ~K m ；
The processor screens out part nouns and sensory adjectives which are the same as the keyword data in the contrast description information to generate a plurality of pieces of contrast characteristic information, and calculates the total number of the contrast characteristic information to be n, wherein the total number is marked as L 1 ~L n ；
The processor calculates the repeated number of the reference characteristic information and the comparison characteristic information as r, and calculates L according to the following formula i And K i Degree of matching P
。
The invention screens out a plurality of reference characteristic information in the reference description information and a plurality of contrast characteristic information in the contrast description information, calculates the matching degree P of the plurality of reference characteristic information and the plurality of contrast characteristic information through a formula, and reflects the contrast characteristic information L through the numerical value of the matching degree P i And reference characteristic information K i So that the registered user can know the kind and name of the disease.
The invention calculates the ratio of r to the total number of the reference characteristic information and the ratio of r to the total number of the comparison characteristic information by calculating the repeated number of the reference characteristic information and the comparison characteristic information as rAnd dividing the result by 2 to obtain a numerical value of the final matching degree P, so that the numerical calculation of the matching degree P is more reasonable, and the matching degree P is a percentage between 0 and 100 percent and can better reflect the comparative characteristic information L i And reference characteristic information K i To a similar degree.
Wherein, the matching degree P is percentage.
For example, referring to fig. 4, the reference description information corresponding to the reference disease data "carpal tunnel syndrome" is the part noun and sensory adjective word in the disease condition that "carpal tunnel syndrome is also called as carpal tunnel stenosis", mouse hand, finger and wrist trauma, fracture, dislocation, sprain or wrist strain and the like cause thickening of transverse carpal ligament, muscle and muscle swelling in the tube, tissue degeneration caused by blood stasis organization or degeneration and proliferation of carpal bone, and reduction of the inner diameter of the tube cavity, thereby pressing the median nerve and causing numbness and weakness of fingers "is selected to obtain K 1 Hand, K 2 Wrist part, K 3 Finger, K 4 Numbness, K 5 Weak, total 5 reference characteristic information K 1 ~K 5 (ii) a Screening out part nouns and sensory type adjectives in the condition that the registered user often feels numbness and weakness in fingers and the fingers feel strong stabbing pain at night corresponding to the comparative description information corresponding to the unknown disease data input by the input module to obtain L 1 Finger, L 2 Numbness, L 3 Stabbing pain, L 4 Weak, 4 contrast characteristic information L 1 ~L 4 (ii) a 5 reference characteristic information K 1 ~K 5 4 pieces of comparison characteristic information L 1 ~L 4 All contain three words of fingers, numbness and weakness, and the matching degree P is calculated according to a formula
=67.5% between the first value of 20% and the second value of 70%, a signal is output that this is possible.
As a variation of the present invention, referring to fig. 1,2, 3, and 4, the database is pre-stored with keyword data;
the processor obtains a plurality of reference features in reference description information corresponding to reference disease dataInformation and marking a plurality of reference characteristic information as K i (ii) a The processor acquires a plurality of pieces of contrast characteristic information in the contrast description information and marks the plurality of pieces of contrast characteristic information as L i (ii) a The processor calculates contrast characteristic information L i And reference characteristic information K i The matching degree P "of (a) is:
the processor screens out part nouns and sensory adjectives which are the same as the keyword data in the reference description information corresponding to the reference disease data and generates a plurality of reference characteristic information, the total number of the reference characteristic information is m, and the reference characteristic information is marked as K 1 ~K m ；
The processor screens out part nouns and sensory adjectives which are the same as the keyword data in the contrast description information to generate a plurality of pieces of contrast characteristic information, and calculates the total number of the contrast characteristic information to be n, wherein the total number is marked as L 1 ~L n ；
The processor calculates the repetition number of the reference characteristic information and the comparison characteristic information as r, and converts the repetition number r into a matching degree P.
The method screens out a plurality of reference characteristic information in the reference description information, screens out a plurality of contrast characteristic information in the contrast description information, calculates the repeated number r of the reference characteristic information and the plurality of contrast characteristic information, converts the repeated number r into the numerical value of the matching degree P, and reflects the contrast characteristic information L according to the numerical value of the matching degree P i And reference characteristic information K i So that the registered user can know the kind and name of the disease.
For example, the first reference disease data is asthma, and the reference characteristic information selected by the processor is: k is 1 Cough, K 2 Asthma, K 3 Obstructed breathing, K 4 Sneezing and K 5 Nasal obstruction, total 5 reference characteristic information K 1 ~K 5 (ii) a The second reference disease data is bronchitis, and the reference characteristic information screened by the processor comprises: k 1 Cough, K 2 Asthma, K 3 Chest distress, 3 reference characteristic information K 1 ~K 3 (ii) a The third reference disease data is pleurisy, and the reference characteristic information screened by the processor is as follows: k 1 Cough, K 2 Chest pain, K 3 Gas urgency, 3 reference characteristic information K 1 ~K 3 (ii) a The comparison characteristic information screened by the processor comprises: l is 1 Cough, L 2 Asthma, 2 pieces of contrast characteristic information L 1 ~L 2 The number of the repeated reference characteristic information and the repeated comparison characteristic information of the first reference disease data asthma is r 1 2, the matching degree P is 2, the repetition number of the reference characteristic information and the comparison characteristic information of the second reference disease data bronchitis is r 2 The number of the reference characteristic information and the comparison characteristic information is 2, the matching degree P is 2, and the repetition number of the reference characteristic information and the comparison characteristic information of the third reference disease data pleurisy is r 3 If the number of the reference data is 1 and the matching degree P is 1, the first reference disease data asthma and the second reference disease data bronchitis are arranged in parallel at the first position, and the third reference disease data pleuritis is arranged at the second position so as to provide the registered user with reference to the possibility of the disease.
As a further explanation of the present invention, referring to fig. 1,2, 3, 4, the first method is: a registered user inputs the illness duration t and the discomfort degree coefficient s through an input module;
the processor generates a correction coefficient f corresponding to the ill condition of the registered user n Outputting corresponding early warning indication T according to the following formula
When the processor outputs disease diagnosis data of a signal possibly suffering from the disease, the correction coefficient corresponding to the disease condition of the registered user is f 1 ；
When the processor outputs disease diagnosis data including a signal possibly suffering from the disease and a signal probably suffering from the disease, the corresponding correction coefficient of the illness condition of the registered user is f 2 ；
The processor judges whether the early warning indication T is smaller than a first early warning threshold value, if so, outputs a first-level early warning level and corresponding recommended content data, reduces the first value and the second value by a first variable, and if not, outputs a second-level early warning level and corresponding recommended content data.
The invention relates to a method for correcting the ill time t, the discomfort degree coefficient s and the correction coefficient f generated by the method, wherein the ill time t is related to the ill condition of the registered user n And substituting the early warning index T into a formula to calculate the corresponding early warning index T, and outputting different early warning grades and recommended content data according to the numerical value of the early warning index T, thereby providing early warning and recommended contents of different grades for the registered user based on different diseased conditions.
The invention only needs to increase the correction coefficient f by utilizing the formula n The weight of (2) is such that the correction coefficient f n The weight of (a) is larger in the sick time length t and the discomfort degree coefficient s, and finally the early warning indication number, the sick time length t, the discomfort degree coefficient s and the correction coefficient f generated by the method are used n Are all positively correlated and the correction factor f n The effect of (c) is greatest.
According to the invention, the processor can output signals possibly suffering from the disease at a lower early warning level by changing the sizes of the first numerical value and the second numerical value, so that the correction coefficient f is changed n The early warning level is increased to a certain extent, so that registered users can pay more attention to possibly suffering diseases and pay more attention to protection at ordinary times.
Wherein the first variable is 5% to 20%, preferably 10%.
The method comprises the following steps of outputting a first-level early warning grade and corresponding recommended content data, and reducing a first variable of a first numerical value and a second numerical value: when the early warning indication T is smaller than a first early warning threshold value or not, the output first-level early warning level is a lower-level early warning level, the first value is 10% by reducing the first value by 10% and the second value by 70%, the second value is 60%, and the left end point and the right end point of the range from the first value to the second value are reduced by 10% of the first variable. For example, when the calculated degree of matching P is 15% out of the range [20%,70% ], the processorAnd outputting a signal that the patient is not suffered from the disease, and after the first value and the second value are both reduced by the first variable, calculating the matching degree P to be 15% in the range of [10%, 60%), and outputting a signal that the patient is possibly suffered from the disease by the processor. That is, by reducing the first variable from the first value and the second value, the processor outputs a signal that may cause the disease even at a lower warning level, thereby changing the correction coefficient f n The early warning level is increased to a certain extent, so that registered users can pay more attention to possibly suffered diseases and pay more attention to protection at ordinary times.
The duration t of the illness is the duration from the occurrence of discomfort symptoms of the illness to the inquiry and diagnosis of the illness of the registered user, and the unit is h.
The discomfort degree coefficient s is based on the subjective feeling degree of the registered user to discomfort at present, and the larger the value of the discomfort degree coefficient s is, the more discomfort the registered user feels and the more difficult the disease to endure is. For example, the discomfort degree coefficient s preferably includes three levels: the primary discomfort is that the discomfort rarely occurs and the normal life is not influenced, and the corresponding primary discomfort degree coefficient s is 1 to 10; the secondary discomfort is occasional attacks with moderate discomfort, and the corresponding secondary discomfort degree coefficient s is 11 to 20; the third-level discomfort is very uncomfortable after frequent attack, and the corresponding coefficient s of the degree of the third-level discomfort is 21 to 30. The registered user can output a specific numerical value of the corresponding discomfort degree grade coefficient s according to the discomfort degree of the registered user.
When the registered user only possibly suffers from a certain disease, the correction coefficient f corresponding to the current disease condition 1 The value is minimum, preferably 2; when the registered user has a high probability of having a certain disease and is likely to have other certain diseases, the correction coefficient f corresponding to the current disease condition 3 The value is maximum, preferably 4.
The larger the processor outputs the early warning indication T, the stricter early warning level is output to the registered user, and the registered user needs to take a doctor at a certain time and pay attention to ordinary maintenance.
The first early warning threshold is 5-50, and preferably 20.
Wherein, the first-level early warning grade is a lower-level early warning grade, and the second-level early warning grade is a higher-level early warning grade.
For example, the duration of illness of the registered user is 20h, the secondary discomfort degree coefficient s is 24, and after the disease inquiry diagnosis, the output disease diagnosis result is: registered users may suffer from hand rheumatoid arthritis. Corresponding correction factor f 2 Is 2, the early warning display number is obtained by substituting the formula
，
If the value is larger than the first early warning threshold value 20, outputting a secondary early warning level and corresponding recommended content data, wherein the recommended content data can be: the treatment department is recommended to treat the rheumatism and immunization department, and the treatment hospital XX is recommended to be treated in the XX hospital, wherein the cautions are as follows: at ordinary times, people pay attention to warm keeping and rest, and are not tired excessively, pungent, spicy, greasy and other stimulating foods are forbidden, and some foods with high protein such as milk, meat, eggs, beans and the like are eaten.
As a further explanation of the present invention, referring to fig. 1,2, and 3, the processor updates the first initial perspective of the primary stereo model and the second initial perspective of the secondary stereo model according to the captured data of the registered user clicking at least one secondary position of the secondary stereo model.
According to the method, the disease inquiring action is influenced next time through the disease inquiring action, so that the time consumed by a registered user for adjusting the initial visual angle of the primary stereo model or the secondary stereo model is reduced or eliminated as much as possible, and the disease inquiring efficiency is improved.
Wherein "the processor updates the first initial perspective of the primary stereo model and the second initial perspective of the secondary stereo model according to the captured at least one secondary position data of the registered user clicking the secondary stereo model" means: for example, when a registered user suffers from a certain disease at the wrist, the angles of the primary stereo model and the secondary stereo model are updated, when the registered user is not suitable for inquiring the disease, the initial visual angle displayed on the primary interface is the primary stereo model with the hand relatively enlarged, the secondary interface is the secondary stereo model with the wrist relatively enlarged, the action of inquiring the disease next time is influenced according to the action of inquiring the disease, so that the time consumed by the registered user for adjusting the initial visual angle of the primary stereo model or the secondary stereo model is reduced or eliminated as much as possible, and the disease inquiry efficiency is improved.
For further explanation of the present invention, referring to fig. 1, when the processor determines that the second login information matches the first login information, the processor can retrieve medical record data, reference disease data, disease diagnosis data, and recommended content data corresponding to the registered user.
According to the invention, through the arrangement, medical record data, reference disease data, disease diagnosis data and recommended content data corresponding to the registered user can be called in advance, and the reference disease data, the disease diagnosis data and the recommended content data can be compared with factors such as gender and age in the medical record data.
For further explanation of the present invention, referring to fig. 1, the processor is electrically connected to the input module and the display module.
Through the arrangement, the processor can be electrically connected with the input module and the display module, so that signal transmission is realized.
For further explanation of the present invention, referring to fig. 1 and 2, the first initial perspective is an initial perspective corresponding to a primary stereo model in a primary interface when a user queries a disease.
Through the arrangement, the user can adjust the first initial visual angle of the primary three-dimensional model so as to find the name of the primary part which the user wants to click.
For further explanation of the present invention, referring to fig. 1 and fig. 3, the second initial perspective is an initial perspective corresponding to a secondary stereoscopic model in a secondary interface when a user queries a disease.
Through the arrangement, the user can adjust the second initial visual angle of the secondary three-dimensional model so as to find the name of the secondary part which the user wants to click.
For further explanation of the present invention, reference is made to fig. 1,2, 3 and 4, where the comparative characteristic information is a description of the registered user about the characteristics of the disease.
Through the arrangement, the user can describe the characteristic that the body of the user feels uncomfortable through a plurality of keywords.
The above-mentioned embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solution of the present invention by those skilled in the art should fall within the protection scope defined by the claims of the present invention without departing from the spirit of the present invention.
Claims (7)
1. The utility model provides a medical treatment big data cloud platform which characterized in that: comprises that
A database in which first login information, medical record data, disease diagnosis data, and recommended content data of a registered user are prestored;
the input module is used for registering the input of second login information and interactive data of a user;
the processor is used for judging whether the second login information is matched with the first login information or not, outputting a repeated login signal if the second login information is not matched with the first login information, and outputting a login success signal if the second login information is matched with the first login information;
the step that the processor can output the disease diagnosis data corresponding to the interactive data according to the interactive data comprises the following steps:
the database is also pre-stored with a primary interface, and the primary interface comprises primary problem data, a primary stereo model and primary position data; the database is also pre-stored with a secondary interface corresponding to the primary position data, and the secondary interface comprises secondary problem data, a secondary three-dimensional model and secondary position data;
the input module is electrically connected with the display module, and the display module is used for displaying a primary interface and a secondary interface;
the display module displays a primary interface and displays a primary three-dimensional model at a first initial visual angle;
the processor acquires first click time of the registered user on the first-level stereo model according to the first-level problem data, judges whether the first click time is smaller than a first preset threshold value, and if so, captures first-level position data of the first-level stereo model clicked by the registered user, controls the display module to display a second interface corresponding to the first-level position data, and displays the second-level stereo model at a second initial view angle;
the processor acquires second click time of the registered user on the secondary three-dimensional model, judges whether the second click time is smaller than a first preset threshold value, and if yes, the processor captures at least one secondary part data of the secondary three-dimensional model clicked by the registered user and outputs disease diagnosis data corresponding to the secondary part data through the first step;
the database also stores reference position data corresponding to the secondary position data, at least one reference disease data corresponding to the reference position data and reference description information corresponding to the reference disease data;
the first step comprises:
the processor acquires a plurality of reference characteristic information in the reference description information corresponding to the reference disease data and marks the plurality of reference characteristic information as K i ；
The user inputs the contrast description information through the input module;
the processor acquires a plurality of pieces of contrast characteristic information in the contrast description information and marks the plurality of pieces of contrast characteristic information as L i ；
The processor calculates contrast characteristic information L i And reference characteristic information K i And determining whether the matching degree P is less than a first value, if so,outputting a signal that the patient does not suffer from the disease; if not, judging whether the matching degree P is between a first value and a second value, and if so, outputting a signal possibly suffering from the disease; if not, outputting a signal with a high probability of suffering from the disease;
the database is prestored with keyword data;
the processor acquires a plurality of reference characteristic information in the reference description information corresponding to the reference disease data and marks the plurality of reference characteristic information as K i (ii) a The user inputs the contrast description information through the input module; the processor acquires a plurality of pieces of contrast characteristic information in the contrast description information and marks the plurality of pieces of contrast characteristic information as L i (ii) a The processor calculates contrast characteristic information L i And reference characteristic information K i The matching degree P "of (a) is:
the processor screens out part nouns and sensory adjectives which are the same as the keyword data in the reference description information corresponding to the reference disease data to generate a plurality of reference characteristic information, and calculates the total number of the reference characteristic information to be m, wherein the reference characteristic information is marked as K 1 ～K m ；
The processor screens out part nouns and sensory adjectives which are the same as the keyword data in the contrast description information to generate a plurality of pieces of contrast characteristic information, and calculates the total number of the contrast characteristic information to be n, wherein the total number is marked as L 1 ～L n ；
The processor calculates the repeated number of the reference characteristic information and the comparison characteristic information as r, and calculates L according to the following formula i And K i Degree of matching P
2. The medical big data cloud platform according to claim 1, wherein:
and the processor updates a first initial view angle of the primary stereo model and a second initial view angle of the secondary stereo model according to at least one captured secondary position data of the registered user clicking the secondary stereo model.
3. The medical big data cloud platform of claim 2, wherein:
and when the processor judges that the second login information is matched with the first login information, the processor can call medical record data, reference disease data, disease diagnosis data and recommended content data corresponding to the registered user.
4. The medical big data cloud platform according to claim 3, wherein:
the processor is electrically connected with the input module and the display module.
5. The medical big data cloud platform according to claim 4, wherein:
the first initial visual angle is an initial visual angle corresponding to a primary stereo model in a primary interface when a user inquires diseases.
6. The medical big data cloud platform according to claim 5, wherein:
and the second initial visual angle is an initial visual angle corresponding to a secondary stereoscopic model in a secondary interface when the user inquires the disease.
7. The medical big data cloud platform according to claim 6, wherein:
the comparison characteristic information is the description of the registered user on the characteristics of the disease.
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