CN113140299A - Medical expert training auxiliary system and auxiliary method - Google Patents
Medical expert training auxiliary system and auxiliary method Download PDFInfo
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Abstract
A culture support system and a support method for a medical expert, the culture support system for the medical expert comprising: a doctor data receiving end for receiving data information of the doctor; the grading module is connected with the doctor data receiving end and used for extracting the effective information, selecting the medical experts meeting the requirements and grading the medical experts; an education center module connected with the grading module and used for proposing questions to the medical experts and matching related professional or hospital answers; the sharing center module is connected with the education center module and is used for data information exchange and knowledge data storage; and the ranking module is connected with the education center module and the sharing center module and is used for ranking the medical experts. A training auxiliary system and an auxiliary method for medical experts can provide hierarchical education and ranking information, and meanwhile, authoritative and rich learning resources are efficiently and accurately provided for the medical experts.
Description
Technical Field
The invention belongs to the field of expert culture, relates to an expert culture system, and particularly relates to a culture auxiliary system and an auxiliary method for medical experts.
Background
In recent years, as the awareness of learning has been increased and terminal devices have become popular, more and more doctors and experts tend to learn on line. Compared with an off-line learning mode of a whole-day system, the on-line learning mode can reduce learning cost, obtain related results efficiently for problems in practice, and simultaneously relieve the problem of lack of education resources, so that the on-line learning method is more and more favored. Meanwhile, the problems encountered in practice can be timely analyzed and solved by online learning, so that the impression can be quickly deepened, the efficiency of answering the problems is high, the speed is high, and basic doctors and patients are helped to solve a lot of problems.
However, the existing medical experts do not have a systematic culture method, and can only search for an answer online when a question is encountered, and can only input basic information of a patient to wait for or answer a relevant doctor when the answer is searched online, the online question-answering system has no authority, cannot judge whether the answer result meets the requirement, cannot upload part of detection results when the question is searched, can only wait for the reply of the online doctor, and has no answer when no doctor replies. This on-line approach may cause misdiagnosis or delay in diagnosis, posing a threat to the health of the patient.
Disclosure of Invention
In view of the above disadvantages of the prior art, an object of the present invention is to provide a system and a method for assisting a medical expert in training, which are used to solve the problems of the prior art, such as lack of authority, inability to upload a part of the test results, and inability to reply in time. The system realizes hierarchical education, and provides authoritative and rich learning resources for the medical experts efficiently and accurately.
In order to achieve the above and other related objects, the present invention provides a system and a method for assisting in the training of a medical professional, the system comprising:
a doctor data receiving end for receiving data information of a plurality of doctors;
the grading module is used for extracting effective information in the doctor data receiving end, selecting the doctor meeting the requirements as a medical expert according to the effective information, and grading the medical expert;
the education center module is used for extracting feature data of the questions proposed by the medical experts, matching corresponding superior experts or couriers for the medical experts according to the feature data, solving the questions proposed by the doctors by the superior experts or the couriers, and showing the solved results by the education center module;
the sharing center module is used for data information communication among the medical experts and between the medical experts and the superior expert or the hospital, and can realize the judgment and storage of new knowledge data;
the ranking module is used for ranking the medical experts according to the influence of doctors to obtain the ranking of the medical experts; wherein the physician influence is related to physician service ability, contribution, medical research level, and/or medical skill ability; and the doctor influence is calculated according to the received activity participated by the doctor
In an embodiment of the present invention, the ranking module includes: the system comprises an information acquisition unit, an information comparison unit and a grading unit; the information acquisition unit is used for extracting effective data of the doctor and transmitting the effective data to the information comparison module, the information comparison unit is used for comparing the effective data of the doctor with required effective data and selecting the cultured medical experts, and the grading unit is used for grading the selected medical experts.
In an embodiment of the present invention, the classification unit includes: an extraction subunit and a grading subunit; the extraction subunit is used for extracting feature data required by the ranking of the medical experts, the grading subunit is used for comparing the feature data with the standard of the feature data in the grading subunit, and the grading subunit obtains the grade of the medical experts according to the comparison result.
In one embodiment of the present invention, the educational center module comprises: the problem receiving unit, the matching unit and the answering unit; the problem receiving unit is used for receiving various kinds of difficult and complicated information of the medical experts, the matching unit is used for flexibly matching experts or academies for solving the difficult and complicated information according to regions or education centers, and the solving unit is used for sharing the solved result of the difficult and complicated information.
In an embodiment of the present invention, the education center module further includes an opinion obtaining unit connected to the answering unit for collecting opinion information of users and general doctors.
In an embodiment of the present invention, the shared center module includes: a knowledge storage unit and a knowledge expansion unit; wherein, the knowledge storage unit is used for storing the existing determined medical knowledge data, and the knowledge expansion unit is used for judging and increasing new knowledge.
In an embodiment of the present invention, the knowledge expansion unit includes: the information publishing sub-unit, the information discussing sub-unit and the information judging sub-unit; the information publishing subunit is used for publishing the new data obtained by each expert, the information discussing subunit is used for collecting the analysis information of each expert on the new data, and the information judging subunit is used for judging the analysis information of the new data.
In one embodiment of the invention, the ranking module comprises an expert confidence data set unit and a ranking unit; the expert data acquisition unit is connected with the education center module and the sharing center module and used for acquiring relevant data of the medical experts, and the ranking unit is used for analyzing various data information of the medical experts according to the weight to obtain the ranking of the medical experts.
In an embodiment of the present invention, the medical expert training assistance system further includes a data storage end, which is connected to the doctor data receiving end, the ranking module, the education center module, the sharing center module, and the ranking module, respectively, and the data storage end is configured to store a plurality of information of a plurality of diseases and information of entered doctors, experts, and academies.
In one embodiment of the invention, the physician influence of each of said activities is calculated according to the following formula:
wherein, Ii-nRepresenting the influence of the doctor obtained after the doctor i participates in the activity n; i ismRepresenting the influence of the doctor before the mth doctor participates in the activity n; m represents the number of all physicians participating in activity n; i isiRepresenting the influence of doctor i before participating in activity n; ω represents a weight coefficient; α is a constant.
The invention also provides a medical expert culture auxiliary method, which at least comprises the following steps:
s1: receiving data information of a doctor through a doctor data receiving end;
s2: extracting effective information in the data information of the doctor through a grading module;
s3: selecting the medical experts meeting the requirements through a grading module and grading the medical experts;
s4: the education center module is used for extracting feature data of the questions posed by the medical experts;
s5: matching corresponding upper-level experts or couriers for the medical experts according to the characteristic data through an education center module, wherein the upper-level experts or the couriers answer the questions proposed by the doctors, and the education center module publicizes the answer results;
s6: data information exchange and knowledge data storage among the medical experts, between the medical experts and the superior expert or the courtyard through a sharing center;
s7: ranking the medical experts through a ranking module according to the influence of doctors to obtain the ranking of the medical experts; wherein the doctor influence is related to doctor service ability, contribution degree, medical research level and/or medical skill ability, and the doctor influence is calculated and obtained according to the received activities participated by the doctor
The invention also provides a medical expert training auxiliary system, which at least comprises:
a doctor data receiving end for receiving data information of a plurality of doctors;
the grading module comprises an information acquisition unit, an information comparison unit and a grading unit; the information acquisition unit is used for extracting effective data of the doctor and transmitting the effective data to the information comparison module, the information comparison unit is used for comparing the effective data of the doctor with required effective data, the information comparison unit selects the cultured medical experts, and the grading unit is used for grading the selected medical experts;
the classification unit includes: an extraction subunit and a grading subunit; the extraction subunit is used for extracting feature data required by the ranking of the medical experts, the grading subunit is used for comparing the feature data with the standard of the feature data in the grading subunit, and the grading subunit obtains the grade of the medical experts according to the comparison result;
the education center module is used for extracting feature data of the questions proposed by the medical experts, matching corresponding superior experts or couriers for the medical experts according to the feature data, solving the questions proposed by the doctors by the superior experts or the couriers, and showing the solved results by the education center module;
the sharing center module is used for data information communication among the medical experts and between the medical experts and the superior expert or the hospital, and can realize the judgment and storage of new knowledge data;
the ranking module is used for ranking the medical experts according to the influence of doctors to obtain the ranking of the medical experts; wherein the doctor influence is related to doctor service ability, contribution, medical research level and/or medical skill ability, and the doctor influence is calculated according to the received activities participated by the doctor. The invention provides a training auxiliary system and an auxiliary method of medical experts.A doctor information is collected through a doctor data receiving end, then the medical experts to be trained are selected through a grading module, and the grading module carries out grading processing on the selected medical experts, so that the medical experts can more accurately select experts for solving questions when the medical experts ask questions; the medical experts can ask questions through the education center module, the education center module can be matched with the most suitable experts or academists to answer the questions, the matching unit in the education center module can accurately find the experts or academists capable of answering the questions, the problem that unmanned answering the questions or answering the questions is delayed is avoided, meanwhile, the opinion acquisition unit exists in the education center module, and in the opinion acquisition unit, except the appointed experts or academists can answer the questions, other doctors, experts or academists can also give own opinions to the questions; a sharing center module provides a platform for exchanging data information for doctors, experts and academists, and simultaneously realizes the storage and expansion of medical knowledge data; ranking of the medical experts can be realized by the ranking module according to various data information of the medical experts, so that the cultivation result of the medical experts is further confirmed.
The present invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a medical expert training assistance method according to the present invention.
The invention also provides electronic equipment which comprises a processor and a memory, wherein the memory stores program instructions, and the processor runs the program instructions to realize the medical expert training auxiliary method.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a block diagram of a medical expert training assistance system.
Fig. 2 is a block diagram of a hierarchical module structure in a medical expert training assistance system.
Fig. 3 is a block diagram showing the construction of an education center module in a medical expert training assistance system.
Fig. 4 is a block diagram of a shared center module in a medical expert training assistance system.
FIG. 5 is a block diagram of a ranking module in the assistant system for training medical experts.
Fig. 6 is a diagram of a neural network architecture.
Fig. 7 is a flowchart of a medical expert training assistance method.
Fig. 8 is a schematic block diagram of a structure of an electronic device.
Fig. 9 is a block diagram of a computer-readable storage medium.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention.
It should be noted that the drawings provided in the present embodiment are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
In recent years, as mobile terminals have become popular, online learning has become a trend. The expert culture auxiliary system and the expert culture auxiliary method provided by the invention can realize efficient and accurate online answering and provide numerous resources for medical education and other aspects. Meanwhile, a systematic auxiliary culture method is provided for learning in other industries, the cultured doctors can be determined through receiving, selecting and grading of doctor data, accurate learning can be achieved according to the grades of the doctors, learning resources can be provided for the doctors in real time through the education center module 3 and the new sharing module 4, and learning results can be better checked through the ranking module 5.
Referring to fig. 1 to 5, in an embodiment of the present invention, a medical expert training assistance system includes a doctor data receiving end 1, a ranking module 2, an education center module 3, a sharing center module 4, and a ranking module 5. Wherein, hierarchical module 2 is connected with doctor data receiving terminal 1, and education center module 3 is connected with hierarchical module 2, and shared center module 4 is connected with education center module 3, and ranking module 5 is connected with shared center module 4 and education center module 3. The grading module 2 comprises an information acquisition unit 21, an information comparison unit 22 and a grading unit 23, the grading unit 23 comprises an extraction subunit 231 and a grading subunit 232, the education center module 3 comprises a question receiving unit 31, a matching unit 32, an answering unit 33 and an opinion obtaining unit 34, the sharing center module 4 comprises a knowledge storage unit 41 and a knowledge expansion unit 42, the knowledge expansion unit 42 comprises an information publishing subunit 421, an information discussion subunit 422 and an information judgment subunit 423, and the ranking module 5 comprises an expert belief data set unit 51 and a ranking unit 52. The medical expert training auxiliary system can also comprise a data storage end 6, wherein the data storage end 6 is bidirectionally connected with a doctor data receiving end 1, a grading module 2, an education center module 3, a sharing center module 4 and a ranking module 5, so that required data can be extracted from the data storage end 6, and the data in the data storage end 6 can also be updated. The connections herein may be through a system such as, but not limited to, cellular, Wi-Fi, picocell, femtocell, bluetooth low energy, near field communication or other wireless communication methods and systems, via any of a variety of wired or wireless computer interactions.
Referring to fig. 1 to 5, in an embodiment of the present invention, a doctor data receiving terminal 1 is a port for receiving data information of a doctor, in the local expert training system provided in the present invention, the doctor needs to input personal information of the doctor to facilitate hierarchical use, and the doctor data receiving terminal 1 can receive various data including information of each party such as text information, picture information, voice information, and video information. Personal information or work information such as hospitals, titles, affiliated disciplines and the like of doctors can be input at the information input end, and personal videos can be uploaded so as to be better understood. The doctor data receiving end 1 receives data uploaded by doctors in real time, the data can be updated, and the data can be modified in time after personal information of the doctors is changed so as to be graded again, and the accuracy of cultivation is improved. Data information of doctors at all levels in all regions is input, so that the construction of the doctor combination body is realized.
Referring to fig. 1 to 5, in an embodiment of the present invention, a grading module 2 is connected to a doctor data receiving end 1, the grading module 2 is configured to extract valid information in the doctor data receiving end 1, the grading module 2 can select a qualified medical expert according to the valid information, and the grading module 2 grades the qualified medical expert. The grading module 2 comprises an information acquisition unit 21, an information comparison unit 22 and a grading unit 23, wherein the information acquisition unit 21 is connected with the doctor data receiving end 1 and used for extracting the effective data of the medical experts and transmitting the effective data to the information comparison module, the information comparison unit 22 is connected with the information acquisition unit 21 and used for comparing the effective data of the medical experts with the required effective data and selecting the cultured medical experts, and the grading unit 23 is connected with the information comparison unit 22 and used for grading the selected medical experts. The classification module 2 picks out the medical experts, and the medical experts are intensively cultured, so that the medical experts can be directly communicated with the academicians.
Referring to fig. 1 to 5, in an embodiment of the present invention, the information collecting unit 21 is connected to the doctor data receiving terminal 1, and the information collecting unit 21 performs effective data extraction on the doctor information received by the doctor data receiving terminal, such as the name, age, job title, history, hospital, and major surgery case of the doctor. There is an associated algorithm in the information collecting unit 21 that can collect the keywords in the doctor input information and transmit the keywords to the information comparing unit 22. The information comparison unit 22 is connected with the data storage terminal 6, the necessary information of the required medical experts is stored in the data storage terminal 6, the extracted keywords are compared with the necessary information in the data storage terminal 6, the doctor information meeting the requirements is stored as the medical experts, and the doctor information not meeting the requirements is deleted. The classification unit 23 is connected to the information comparison unit 22 and the data storage 6, the data storage 6 has a classification standard of the medical experts, and the extracted key information is compared with the classification standard to classify the selected medical experts, for example, the medical experts can be classified into a base level, a prefecture level, a city level, a provincial level and a hospital level. Dividing the medical experts into a plurality of grades provides convenience for searching for the matching of experts or academies for solving the problem subsequently, for example, when the medical experts propose a problem and have no requirement of communicating with the academies, when the medical experts proposing the problem are in the grade of the basic level, the expert which is firstly selected to be solved is a district-level expert. The medical expert who proposes the problem is matched with the prefecture level expert which is closest to the medical expert, the mode can provide the medical expert with the closest educational resources, offline communication can be carried out under the condition, and the cultivation of the medical expert is effectively improved.
Referring to fig. 1 to 5, in an embodiment of the present invention, the education center module 3 includes a question receiving unit 31, a matching unit 32 and a solving unit 33, wherein the question receiving unit 31 is used for receiving various problem information of the medical specialist, and the medical specialist can input patient information and detection information into the question receiving unit 31 when encountering an unresolvable problem. The question receiving unit 31 may receive the linguistic descriptive information of the medical expert, which may include the user's gender, age, place of residence, disease history, genetic history, allergy history, medication history, and so on, and may also include external information such as season, temperature, humidity, infectious disease outbreak, and so on. The problem receiving unit 31 may further include a detection report receiving subunit, configured to obtain a detection report of the user; and the detection report identification subunit is connected with the detection report receiving unit and is used for identifying the detection report to obtain corresponding health information. The medical image receiving subunit is used for acquiring a medical image of a user; and the medical image identification subunit is connected with the medical image receiving unit and is used for identifying the medical image to obtain corresponding health information, and the information provided by the medical expert can be completely received through the problem receiving unit 31.
Referring to fig. 1 to 5, in an embodiment of the present invention, the matching unit 32 of the education center module 3 is used for flexibly matching the experts or the institutions answering the problematic information according to the area or the education center. When the medical expert who raised the question does not select the direct hospital but merely raises the question, the matching unit 32 matches the expert or the hospital who solved the question according to the grade of the medical expert who raised the question and the type and difficulty of the question raised, and the expert who solved the question is preferably an expert who is one level higher than the medical expert in the area. For example, the expert who raised the question belongs to a district-level expert, the matching unit 32 preferably selects the expert for which to solve the question as a city-level expert, and first selects the city-level expert in the city in which the district is located as the expert for which to solve the question. The matching principle can select the expert closest to the medical expert who proposes the question, and the expert at the higher level can answer the question proposed by the medical expert and invite the matched expert at the city level to perform offline explanation. The medical specialist may also specify that the problem that he or she presented is to be solved directly by the institution, and the matching unit 32 selects the most appropriate institution-specific help solution for the category of the identified problem. The flow of matching the answers of the specified experts or the academies can find out the expert or the academies which are most suitable for answering the question, and the expert information of the answer of the question can be quickly obtained so as to efficiently obtain the answer of the question.
In a preferred embodiment of the present invention, first, the type of the problem is determined according to the proposed problem; and finally, selecting a medical expert which is at least one level higher than the questioning doctor for answering the questions according to the grade of the doctor who proposes the questions. It should be noted that, only one method for matching medical experts is given here, but the matching of medical experts is not limited to this one form, and any method for matching medical experts according to the type of question and the level of doctor is within the scope of the present invention.
Referring to fig. 1 to 5, in an embodiment of the invention, the education center module 3 includes an answering unit 33, and the answering unit 33 is used for sharing the answering result of the problem information. In the solution unit 33, the expert or the institution who matched the solution question by the matching unit 32 can perform the solution of the question therein, which is disclosed on the solution system. Meanwhile, the education center module 3 further includes an opinion obtaining unit 34 connected to the answering unit 33 for collecting opinion information of the user and general doctors. The opinion acquisition unit 34 is a unit where all doctors in the system can post their opinions, which can collect different insights of different doctors to be referred to by the medical specialist who presented the problem.
Referring to fig. 1 to 5, in an embodiment of the present invention, the shared center module 4 includes a knowledge storage unit 41 and a knowledge expansion unit 42, wherein the knowledge expansion unit 42 includes an information publishing subunit 421, an information discussion subunit 422, and an information determining subunit 423. The knowledge storage unit 41 is configured to store existing determined medical knowledge data, where the knowledge storage unit 41 includes related knowledge of a disease, and may include data such as a definition of a disease, a symptom of a disease, a detection index, a treatment method of a disease, and a correlation between parameters, and may further include conference videos of experts or institutions, published articles about disease knowledge, and the like.
Referring to fig. 1 to 5, in an embodiment of the present invention, an information issuing subunit 421 is used for issuing new data obtained by each expert, and in the information issuing subunit 421, a doctor, an expert or a hospital in a system may issue relevant information about a disease, including information about disease, such as manifestation of the disease, a diagnosis method of the disease, and treatment of a special case. The information discussion subunit 422 is used for collecting the analysis information of each expert on the new data, and the information discussion subunit 422 collects the opinions about the released information; the information judgment subunit 423 is configured to judge the analysis information of the new data, and the information judgment unit needs to present the relevant certification material and document for the publisher or other expert institutions to certify the published information, for example, a new judgment method for a disease, medication, etc., until the institutions are affirmative. The information judging subunit 423 is connected to the knowledge storage unit 41, and when the released data is approved by the courtyard, the information judging unit transfers the information to the knowledge storage unit 41 to be stored as a conventional technology. The mode can increase the existing medical knowledge data, and the knowledge surfaces of more doctors, experts and academists are expanded.
Referring to fig. 1 to 5, in an embodiment of the present invention, the ranking module 5 includes an expert data collecting unit 51 and a ranking unit 52; the expert data collecting unit 51 is used for collecting the activities of the doctor through the doctor data receiving end. The ranking unit 52 is used for calculating the corresponding doctor influence according to the activities participated by the doctor and ranking the doctor according to the doctor influence. Wherein, the activities and the influence of doctors are related to the influence of doctors and the service ability, contribution degree, medical research level and/or medical skill ability of doctors. Wherein the content of the first and second substances,
1) doctor service ability: the number of issued resources, the number of times of resource transmission, and the interaction between the doctor and the residents related to the doctor include, but are not limited to: uploading case volume, uploading education video volume, uploading academic article volume, uploading knowledge original volume, number of browsed published cases, number of browsed published videos, number of browsed published academic articles, answering case volume, number of common people signed by doctors, disease pre-warning processing of family doctors, health inquiry processing of family doctors, number of common people associated with health consultants, disease pre-warning processing of health consultants, health consultant processing, health consultants giving health management plans to common people, and the like;
2) contribution to the overall system: in the system, the number of cases is labeled, the frequency of science popularization of diseases is increased, and the like;
3) medical research level: the degree to which the doctor learns about the resources in the system, the number of times to log in to the server, and the degree to which the doctor contributes to academic research and meetings; including but not limited to: submitting inquiry case number, video learning times, article learning times, login times, submitting product application feedback, initiating research subjects, initiating academic conferences and the like;
4) the medical skill: the professional background of the doctor and the data completeness of the doctor are indicated; including but not limited to: doctor grade, school calendar, graduation school, qualification certification, completion of filling in existing information, and the like.
Activities, not limited to one, include a very large number of contents, and are related to doctor service ability, contribution degree, medical research level and/or medical skill, such as logging in a server, uploading data, and case labeling, etc., which have been mentioned above, and thus are not described in detail herein. Furthermore, since the time for the doctor to participate in the activity through the medical terminal is not constant, the doctor influence is calculated for each activity in order to accurately evaluate the doctor influence:
wherein, Ii-nRepresenting the influence of the doctor obtained after the doctor i participates in the activity n; i ismIndicating the physician influence of the mth physician participating in activity n; m represents the number of all physicians participating in activity n; i isiRepresenting the influence of doctor i before participating in the activity; omega represents a weight coefficient, is related to activities, corresponds to different weights in different activities; α is a constant.
Further, over time, it is not possible for a physician to engage in only one activity. Then the physician's influence on the participation of the physician in each activity during the preset time is: i isit＝Ii-1+Ii-2+Ii-3+…+Ii-n(ii) a Wherein, IitRepresenting the influence of the doctor obtained by the doctor i within a preset time t; n denotes the doctorThe number of activities in each activity that the student i participates in; i isi-nRepresenting the doctor's influence obtained by the doctor i engaging in the activity n within the preset time t.
In addition, in order to better match reality, the attenuation factor is also considered in the present embodiment when updating the influence of the doctor. Over time, the physician's influence may decline somewhat. Therefore, when calculating the doctor influence of the doctor, the doctor influence by the participation of the doctor is added to the original doctor influence, and a value of attenuation of the doctor influence with time is subtracted.
Referring to fig. 1 to 7, in an embodiment of the present invention, the medical expert training system further includes a data storage end 6 connected to the doctor data receiving end 1, the grading module 2, the education center module 3, the sharing center module 4, and the ranking module 5. The data storage end 6 is used for storing various information of various diseases and information of entered doctors, experts and academists.
The invention also provides a medical expert culture auxiliary method, which at least comprises the following steps:
s1: receiving data information of a doctor through a doctor data receiving end;
s2: extracting effective information in the data information of the doctor through a grading module;
s3: selecting the medical experts meeting the requirements through a grading module and grading the medical experts;
s4: the education center module is used for extracting feature data of the questions posed by the medical experts;
s5: matching corresponding upper-level experts or couriers for the medical experts according to the characteristic data through an education center module, wherein the upper-level experts or the couriers answer the questions proposed by the doctors, and the education center module publicizes the answer results;
s6: data information exchange and knowledge data storage among the medical experts, between the medical experts and the superior expert or the courtyard through a sharing center;
s7: ranking the medical experts through a ranking module according to the influence of doctors to obtain the ranking of the medical experts; wherein the doctor influence is related to doctor service ability, contribution, medical research level and/or medical skill ability, and the doctor influence is calculated according to the received activities participated by the doctor.
Referring to fig. 8, the embodiment further provides a computer-readable storage medium 7, where the computer-readable storage medium 7 stores computer instructions 71, and the computer instructions 71 are used for enabling the medical expert training assistance method. The computer readable storage medium 7 may be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system or propagation medium. The computer-readable storage medium 7 may also include a semiconductor or solid state memory, magnetic tape, a removable computer diskette, a Random Access Memory (RAM), a read-only memory (ROM), a rigid magnetic disk and an optical disk. Optical disks may include compact disk-read only memory (CD-ROM), compact disk-read/write (CD-RW), and DVD.
Referring to fig. 9, the present invention further provides an electronic device, which includes a processor 8 and a memory 9, where the memory 9 stores program instructions, and the processor 8 executes the program instructions to implement the above-mentioned method for assisting in training medical experts. The Processor 8 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; or a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component; the Memory 9 may include a Random Access Memory (RAM), and may further include a Non-Volatile Memory (Non-Volatile Memory), such as at least one disk Memory. The Memory 9 may also be an internal Memory of Random Access Memory (RAM) type, and the processor 8 and the Memory 9 may be integrated into one or more independent circuits or hardware, such as: application Specific Integrated Circuit (ASIC). It should be noted that the computer program in the memory 9 can be implemented in the form of software functional units and stored in a computer readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, an electronic device, or a network device) to perform all or part of the steps of the method according to the embodiments of the present invention.
Referring to fig. 1 to 8, according to the present invention, a system and a method for assisting in training medical experts are provided, a data receiving end 1 of a doctor receives data information of the doctor, a grading module 2 extracts effective information from the data receiving end of the doctor, the grading module 2 selects a medical expert meeting requirements according to the effective information, and the grading module 2 grades the medical expert meeting composite requirements; the education center module 3 is used for extracting feature data of the questions proposed by the medical experts, matching corresponding superior experts or couriers for the medical experts according to the feature data, solving the questions proposed by the doctors by the superior experts or the couriers, and showing the solved results by the education center module 3; the sharing center module 4 is used for data information communication among the medical experts and between the medical experts and the superior expert or the hospital, and the sharing center module 4 can realize knowledge data storage and updating; the ranking module 5 is used for ranking the medical experts according to the influence of doctors to obtain the ranking of the medical experts; wherein the doctor influence is related to doctor service ability, contribution, medical research level and/or medical skill ability, and the doctor influence is calculated according to the received activities participated by the doctor. The medical expert training auxiliary system and the method provided by the invention realize the hierarchical education of the system, and simultaneously, authoritative and rich learning resources are efficiently and accurately provided for medical experts.
The above description is only a preferred embodiment of the present application and a description of the applied technical principle, and it should be understood by those skilled in the art that the scope of the present invention related to the present application is not limited to the technical solution of the specific combination of the above technical features, and also covers other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept, for example, the technical solutions formed by mutually replacing the above features with (but not limited to) technical features having similar functions disclosed in the present application.
Other technical features than those described in the specification are known to those skilled in the art, and are not described herein in detail in order to highlight the innovative features of the present invention.
Claims (11)
1. A medical expert training assistance system, characterized in that it comprises at least:
a doctor data receiving end for receiving data information of a plurality of doctors;
the grading module is used for extracting effective information in the doctor data receiving end, selecting the doctor meeting the requirements as a medical expert according to the effective information, and grading the medical expert;
the education center module is used for extracting feature data of the questions proposed by the medical experts, matching corresponding superior experts or couriers for the medical experts according to the feature data, solving the questions proposed by the doctors by the superior experts or the couriers, and showing the solved results by the education center module;
the sharing center module is used for data information communication among the medical experts and between the medical experts and the superior expert or the hospital, and can realize the judgment and storage of new knowledge data;
the ranking module is used for ranking the medical experts according to the influence of doctors to obtain the ranking of the medical experts; wherein the physician influence is related to physician service ability, contribution, medical research level, and/or medical skill ability; and the doctor influence is calculated based on the received activity the doctor attends.
2. A medical expert training assistance system as claimed in claim 1 wherein the ranking module comprises: the system comprises an information acquisition unit, an information comparison unit and a grading unit; the information acquisition unit is used for extracting effective data of the doctor and transmitting the effective data to the information comparison module, the information comparison unit is used for comparing the effective data of the doctor with required effective data, the information comparison unit selects the cultured medical experts, and the grading unit is used for grading the selected medical experts.
3. A medical expert training assistance system according to claim 2 wherein the ranking unit comprises: an extraction subunit and a grading subunit; the extraction subunit is used for extracting feature data required by the ranking of the medical experts, the grading subunit is used for comparing the feature data with the standard of the feature data in the grading subunit, and the grading subunit obtains the grade of the medical experts according to the comparison result.
4. A medical expert training assistance system as claimed in claim 1 wherein the educational center module comprises: the problem receiving unit, the matching unit and the answering unit; the problem receiving unit is used for receiving various kinds of difficult and complicated information of the medical experts, the matching unit is used for flexibly matching experts or academies for solving the difficult and complicated information according to regions or education centers, and the solving unit is used for sharing the solved result of the difficult and complicated information.
5. A medical expert training assistance system according to claim 1 wherein the shared central module comprises: a knowledge storage unit and a knowledge expansion unit; wherein, the knowledge storage unit is used for storing the existing determined medical knowledge data, and the knowledge expansion unit is used for judging and increasing new knowledge.
6. The system of claim 4, wherein the knowledge expansion unit comprises: the information publishing sub-unit, the information discussing sub-unit and the information judging sub-unit; the information publishing subunit is used for publishing the new data obtained by each expert, the information discussing subunit is used for collecting the analysis information of each expert on the new data, and the information judging subunit is used for judging the analysis information of the new data.
7. A medical expert training assistance system according to claim 1, wherein the ranking module includes an expert data acquisition unit and a ranking unit; the expert data acquisition unit is connected with the education center module and the sharing center module and used for acquiring relevant data of the medical experts, and the ranking unit is used for analyzing various data information of the medical experts according to the weight to obtain the ranking of the medical experts.
8. The system of claim 7, further comprising a data storage end connected to the doctor data receiving end, the ranking module, the education center module, the sharing center module and the ranking module, wherein the data storage end is used for storing a plurality of information of a plurality of diseases and information of entered doctors, experts and academies.
9. A medical expert training assistance system according to claim 1 wherein the physician influence of each of the activities is calculated according to the following formula:
wherein, Ii-nRepresenting the influence of the doctor obtained after the doctor i participates in the activity n; i ismRepresenting the influence of the doctor before the mth doctor participates in the activity n; m represents the number of all physicians participating in activity n; i isiRepresenting the influence of doctor i before participating in activity n; ω represents a weight coefficient; α is a constant.
10. A medical expert culture assistance method is characterized by at least comprising the following steps:
s1: receiving data information of a doctor through a doctor data receiving end;
s2: extracting effective information in the data information of the doctor through a grading module;
s3: selecting the medical experts meeting the requirements through a grading module and grading the medical experts;
s4: the education center module is used for extracting feature data of the questions posed by the medical experts;
s5: matching corresponding upper-level experts or couriers for the medical experts according to the characteristic data through an education center module, wherein the upper-level experts or the couriers answer the questions proposed by the doctors, and the education center module publicizes the answer results;
s6: data information exchange and knowledge data storage among the medical experts, between the medical experts and the superior expert or the courtyard through a sharing center;
s7: ranking the medical experts through a ranking module according to the influence of doctors to obtain the ranking of the medical experts; wherein the doctor influence is related to doctor service ability, contribution, medical research level and/or medical skill ability, and the doctor influence is calculated according to the received activities participated by the doctor.
11. A medical expert training assistance system, characterized in that it comprises at least:
a doctor data receiving end for receiving data information of a plurality of doctors;
the grading module comprises an information acquisition unit, an information comparison unit and a grading unit; the information acquisition unit is used for extracting effective data of the doctor and transmitting the effective data to the information comparison module, the information comparison unit is used for comparing the effective data of the doctor with required effective data, the information comparison unit selects the cultured medical experts, and the grading unit is used for grading the selected medical experts;
the classification unit includes: an extraction subunit and a grading subunit; the extraction subunit is used for extracting feature data required by the ranking of the medical experts, the grading subunit is used for comparing the feature data with the standard of the feature data in the grading subunit, and the grading subunit obtains the grade of the medical experts according to the comparison result;
the education center module is used for extracting feature data of the questions proposed by the medical experts, matching corresponding superior experts or couriers for the medical experts according to the feature data, solving the questions proposed by the doctors by the superior experts or the couriers, and showing the solved results by the education center module;
the sharing center module is used for data information communication among the medical experts and between the medical experts and the superior expert or the hospital, and can realize the judgment and storage of new knowledge data;
the ranking module is used for ranking the medical experts according to the influence of doctors to obtain the ranking of the medical experts; wherein the doctor influence is related to doctor service ability, contribution, medical research level and/or medical skill ability, and the doctor influence is calculated according to the received activities participated by the doctor.
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