CN111028958A - Expert collaborative diagnosis system, method, device and computer readable medium - Google Patents
Expert collaborative diagnosis system, method, device and computer readable medium Download PDFInfo
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- CN111028958A CN111028958A CN201911217692.4A CN201911217692A CN111028958A CN 111028958 A CN111028958 A CN 111028958A CN 201911217692 A CN201911217692 A CN 201911217692A CN 111028958 A CN111028958 A CN 111028958A
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- 238000003745 diagnosis Methods 0.000 title claims abstract description 70
- 238000000034 method Methods 0.000 title claims abstract description 20
- 208000035977 Rare disease Diseases 0.000 claims abstract description 61
- 201000010099 disease Diseases 0.000 claims abstract description 47
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 47
- 238000011282 treatment Methods 0.000 claims abstract description 22
- 239000003814 drug Substances 0.000 claims description 6
- 229940079593 drug Drugs 0.000 claims description 5
- 238000011160 research Methods 0.000 claims description 3
- 208000024891 symptom Diseases 0.000 claims description 3
- 230000008506 pathogenesis Effects 0.000 claims 1
- 230000008569 process Effects 0.000 abstract description 5
- 230000003340 mental effect Effects 0.000 abstract description 3
- 238000007726 management method Methods 0.000 description 30
- 238000012550 audit Methods 0.000 description 3
- 238000003759 clinical diagnosis Methods 0.000 description 3
- 108090000623 proteins and genes Proteins 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
- 238000011269 treatment regimen Methods 0.000 description 2
- 208000032170 Congenital Abnormalities Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001684 chronic effect Effects 0.000 description 1
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- 230000003412 degenerative effect Effects 0.000 description 1
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- 238000001514 detection method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000013399 early diagnosis Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
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- 230000036244 malformation Effects 0.000 description 1
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- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
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Abstract
The invention discloses an expert cooperative diagnosis system based on a rare disease knowledge base, which comprises an expert management module, a diagnosis module and a diagnosis module, wherein the expert management module is used for managing expert information participating in cooperative diagnosis; the patient management module is used for managing the patient information of the rare diseases; the disease knowledge management module is used for managing knowledge information of diseases; the cooperative hospital management module is used for managing cooperative hospital information participating in cooperative diagnosis; the cooperation center management module is used for managing the rare disease cooperation center information participating in the cooperation diagnosis; and the statistical report module is used for counting the patient information of the rare diseases. The invention also discloses an expert cooperative diagnosis method based on the rare disease knowledge base, equipment and a computer readable medium. The invention optimizes the diagnosis process, improves the diagnosis efficiency and the diagnosis accuracy, greatly shortens the diagnosis time of rare diseases, wins the best treatment opportunity for patients and simultaneously lightens the economic and mental burden of families of patients.
Description
Technical Field
The invention relates to the technical field of medical information internet, in particular to an expert collaborative diagnosis system, method, equipment and computer readable medium based on a rare disease knowledge base.
Background
The rare diseases refer to diseases with extremely low incidence rate, and according to the definition of the world health organization, the rare diseases refer to the diseases with the sick people accounting for 0.65-1 per mill of the general population. Many rare diseases are genetically caused and are generally chronic, progressive, degenerative and life threatening. Patients affected by rare diseases often suffer from a variety of attendant medical complications and present with a variety of symptomatic deformities. For rare diseases, the assessment of malformations by experienced experts is often a key factor in identifying rare diseases, and diagnosis and corresponding treatment planning by combining phenotypic information and genetic data information are often needed.
Although the incidence rate of the rare diseases is not high, China is a large population country, the number of the rare diseases is not small under the condition of a huge population base, and the total number of the population reaches tens of millions according to preliminary statistics. At present, the diagnosis of the rare diseases in China is mainly focused on a few hospitals in the first-line large city, and the rare patients are distributed all over the country. Patients in various places need to seek medical advice step by step and roll over for multiple places to reach a large hospital in the same line for diagnosis and treatment, which greatly delays the best treatment opportunity and causes huge economic and mental burden to the patients and families.
Moreover, in the rare disease diagnosis process, hospitals often need to provide partial diagnosis records and gene samples of patients to gene testing companies of third parties for analysis and diagnosis, the third party testing companies return a paper report to the hospitals, doctors often have various questions about the diagnosis report, such as incorrect or incomplete phenotype sorted from the diagnosis records by the third party testing companies, insufficient match between the pathogenic genes and the phenotype observed by the doctors, and the like. Communication with a third-party detection company is required again, and the diagnosis time of the patient is prolonged.
Due to the rarity of the disease, the scarcity of experienced specialists, and the complexity of clinical diagnosis, it is often not possible to properly and fully train a large number of physicians distributed throughout the world with a lack of relevant awareness, knowledge, and experience.
Therefore, how to use computer software, hardware, network communication equipment and other cooperative equipment to perform online accurate prevention, diagnosis and treatment on rare diseases and shorten the treatment time and economic cost of patients is a technical problem to be solved by those skilled in the art.
Meanwhile, with the increasingly accelerated medical informatization construction, the types and scales of information such as medical data are increasing, and in the clinical diagnosis process, the medical data information includes the following types: the first is a basic knowledge base, which refers to the 'static' rule knowledge of reasonable medicine, medical formula, medical term set, etc.; the second is a clinical diagnosis knowledge base, which is formed by continuous manual summarization and comprises clinical paths, clinical guidelines, a disease diagnosis and treatment knowledge base and the like; thirdly, reference is needed to be provided by reference documents, particularly domestic and foreign reference documents for diagnosis and treatment of rare diseases; and fourthly, mining the formed knowledge from historical cases. However, some of the data belong to large files and some belong to small files, and in the face of the growing mass of medical data, how to better store and facilitate the subsequent efficient analysis and use is also a difficult problem.
Disclosure of Invention
In view of this, the embodiments of the present disclosure provide an expert collaborative diagnosis system, method, device and computer-readable medium based on a rare disease knowledge base, which are used to solve the problems of low efficiency of rare disease diagnosis and lack of doctor resources with relevant experience in various regions in the prior art.
The invention provides an expert collaborative diagnosis system based on a rare disease knowledge base, which comprises an expert management module, a patient management module, a disease knowledge management module, a collaborative hospital management module, a collaboration center management module and a statistical report module, wherein the expert management module manages expert information participating in collaborative diagnosis; the patient management module manages the patient information of the rare diseases; the disease knowledge management module manages knowledge information of diseases; the cooperative hospital management module manages cooperative hospital information participating in cooperative diagnosis; the cooperation center management module manages rare disease cooperation center information participating in cooperation diagnosis; and the statistical report module is used for counting the patient information of the rare diseases.
Further, the expert information includes, but is not limited to, expert basic information, expert expertise, expert research topics, major published papers, and expert medical contributions.
Further, the patient information includes, but is not limited to, patient basic information, past medical history, case information, and disease treatment information.
Further, the knowledge information of the disease includes, but is not limited to, the name of the disease, the classification of the disease, the cause of the disease, the symptoms of the disease, the treatment regimen, and the instructions for medication.
Further, the collaborative hospital information includes, but is not limited to, collaborative hospital name, collaborative hospital code, collaborative hospital zone, and collaborative hospital type.
Further, the rare disease collaboration center information includes, but is not limited to, a center creator, a center principal, originating hospital information, collaboration expert information, rare disease diagnosis information, and treatment plan information.
Further, the facility environment in which the expert collaborative diagnosis system operates includes an application server, a database layer and a base server layer.
Meanwhile, the invention also provides an expert cooperative diagnosis method based on the rare disease knowledge base, which comprises the following steps: step 1: generating expert information; step 2: generating patient information; and step 3: generating disease knowledge information; and 4, step 4: generating cooperative hospital information; and 5: generating a rare disease collaboration center.
Meanwhile, the invention also provides expert cooperative diagnosis equipment based on the rare disease knowledge base, which comprises: a processor; a memory for storing executable instructions of the processor; wherein the processor is configured to perform the above-described system or method via execution of the executable instructions.
The present invention also provides a computer readable medium for storing computer readable instructions which, when executed, implement the above-described system or method.
The invention has the beneficial effects that: the embodiment provided by the invention is deployed at the cloud, and doctors carry out cooperative diagnosis at any time and any place through means such as a PC (personal computer), a mobile phone and the like, so that the diagnosis process is optimized, the diagnosis efficiency and the diagnosis accuracy are improved, a powerful support is provided for early diagnosis of patients, rare patients do not need to seek medical treatment at four places, the diagnosis time of rare diseases is greatly shortened, the optimal treatment time is won for the patients, and the economic and mental burdens of families of the patients are relieved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic structural diagram of an expert collaborative diagnosis system based on a rare disease knowledge base according to an embodiment of the present invention; and
fig. 2 is an expert cooperative diagnosis method based on a rare disease knowledge base provided in an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.
The invention provides an expert cooperative diagnosis system based on a rare disease knowledge base, as shown in figure 1 of the accompanying drawings, the facility environment for the operation of the expert cooperative diagnosis system is composed of an application program server, a database layer and a basic server layer, the system adopts a B/S architecture, follows a J2EE multi-layer architecture mode, and is specifically realized by a presentation layer, a service layer and a persistence layer, so that the portability of the system is ensured, and the compatibility and the expansibility of the system are enhanced.
The application program server is a basic environment for the operation of the whole system module, and integrates the functions of cache management, thread management, connection pool management, safety authentication management and the like. Due to the system independence and standardization of J2EE, the system of the present invention can be ported between different application servers.
The database layer is the database foundation of the system, and the business processes are all performed around the data. Due to the adoption of a standard data interface, the system can run on different database systems.
The basic server layer provides basic guarantee for system operation, and the cross-platform property of J2EE ensures that the system can be safely transplanted among different operating systems.
The expert collaborative diagnosis system comprises the following modules:
and the expert management module manages the expert information participating in the collaborative diagnosis. The expert information comprises but is not limited to expert basic information, expert excellence fields, expert research topics, main published papers, expert medical contributions and the like, and the expert management module can perform operations of adding, deleting, modifying and inquiring the expert information.
A patient management module that manages patient information for rare diseases. The patient information includes, but is not limited to, patient basic information including patient name, age, sex, region, occupation, contact information, disease treatment information including patient visit time, disease name, medication condition, treatment period, etc., past medical history, case information, disease treatment information, etc. The patient management module can perform operations of adding, deleting, modifying and inquiring the patient information.
And the disease knowledge management module manages knowledge information of the disease. The knowledge information of the disease includes, but is not limited to, the name of the disease, the classification of the disease, the cause of the disease, the symptoms of the disease, the treatment regimen, and the instructions for medication. The disease knowledge management module can perform operations of adding, deleting, modifying and inquiring knowledge information of the diseases.
And the cooperative hospital management module is used for managing the cooperative hospital information participating in the cooperative diagnosis. The collaborative hospital information includes, but is not limited to, a collaborative hospital name, a collaborative hospital code, a collaborative hospital region, a collaborative hospital type, and the like. The cooperative hospital management module can perform operations of adding, deleting, modifying and inquiring the cooperative hospital information.
And the cooperation center management module is used for managing the rare disease cooperation center information participating in the cooperation diagnosis. The rare disease collaboration center information includes, but is not limited to, a center creator, a center principal, originating hospital information, collaboration expert information, rare disease diagnosis information, treatment plan information, and the like. The collaboration center management module can perform operations of adding, deleting, modifying and inquiring the collaboration center information.
And the statistical report module is used for counting the patient information of the rare diseases. The statistical report module can generate corresponding report information according to the age, sex, region, occupation and other dimensions of the patient.
The invention also provides an expert cooperative diagnosis method based on the rare disease knowledge base, as shown in the attached figure 2, the method comprises the following steps:
1. generating expert information: and the expert adds or modifies expert information through the expert management module, a system administrator audits whether the expert information is qualified, and unqualified expert information needs to be modified again until the expert administrator audits to be qualified.
2. Generating patient information: and a system administrator and the experts who pass the examination can add, modify, inquire or delete the patient information of the rare diseases through the patient management module.
3. And (3) generating disease knowledge information: and the system administrator and the experts who pass the examination can add, modify, inquire or delete the knowledge information of the rare diseases through the disease knowledge management module.
4. Generating cooperative hospital information: and both a system administrator and the experts who pass the examination can add, modify, inquire or delete the cooperative hospital information through the cooperative hospital management module.
5. Generating a rare disease collaboration center: the expert who passes the audit establishes or participates in the information of the cooperation center of a certain rare disease through the cooperation center management module, the expert can check the information of the cooperation center which is established and participated in by the expert, and can also invite other experts to participate in the cooperation center, so that the experts can participate in the disease diagnosis of the certain rare disease together, guide the medication or the subsequent treatment of a patient and provide information such as a treatment scheme.
In addition, the experts who pass the examination can also count the patient information through the statistical report module, for example, the age of the patient can be selected to generate the information of the number of patients with different ages of the disease; selecting the sex of the patient to generate a histogram of the male and female proportion of the disease; selecting the region of the patient to generate histogram information of different regions of the disease; selecting the occupation of the patient can check the disease information histogram of the disease in different occupation, and can further check the information of the patient with the disease by clicking the disease information histogram.
In conclusion, the invention integrates medical resources of a first-line large hospital, the power of experts of the large hospital drives the improvement of the technical level of a basic medical institution, a division-labor cooperation mechanism between a general department and other specialist physicians is established, resources of all parties are reasonably utilized, the prevention is mainly realized, the general department first diagnosis and graded diagnosis and treatment are supported, and a precise management type medical service system is practiced, so that a rare patient does not need to seek medical doctors all around, the diagnosis time of rare diseases is greatly shortened, the reform trend of national graded diagnosis and treatment is complied with, and the medical resources are more reasonably applied.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Technical contents not described in detail in the present invention belong to the well-known techniques of those skilled in the art.
Although illustrative embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, and various changes may be made apparent to those skilled in the art as long as they are within the spirit and scope of the present invention as defined and defined by the appended claims, and all matters of the invention which utilize the inventive concepts are protected.
Claims (10)
1. An expert cooperative diagnosis system based on a rare disease knowledge base is characterized by comprising an expert management module, a patient management module, a disease knowledge management module, a cooperative hospital management module, a cooperative center management module and a statistical report module,
the expert management module manages expert information participating in the collaborative diagnosis;
the patient management module manages the patient information of the rare diseases;
the disease knowledge management module manages knowledge information of diseases;
the cooperative hospital management module manages cooperative hospital information participating in cooperative diagnosis;
the cooperation center management module manages rare disease cooperation center information participating in cooperation diagnosis; and
and the statistical report module is used for counting the patient information of the rare diseases.
2. The expert collaborative diagnosis system based on rare diseases knowledge base of claim 1, wherein the expert information includes but is not limited to expert basic information, expert expertise areas, expert research topics, major published papers and expert medical contributions.
3. The expert collaborative diagnosis system based on rare diseases knowledge base of claim 1, wherein the patient information includes but is not limited to basic patient information, past medical history, case information and disease treatment information.
4. The expert collaborative diagnosis system based on rare diseases knowledge base of claim 1, wherein the knowledge information of diseases includes but is not limited to disease name, disease classification, pathogenesis, disease symptom, treatment scheme and medication guide.
5. The expert collaborative diagnosis system based on rare disease knowledge base according to claim 1, wherein the collaborative hospital information includes but is not limited to collaborative hospital name, collaborative hospital code, collaborative hospital region and collaborative hospital type.
6. The expert collaborative diagnosis system based on rare disease knowledge base according to claim 1, wherein the rare disease collaboration center information includes, but is not limited to, center creator, center principal, originating hospital information, collaboration expert information, rare disease diagnosis information, and treatment plan information.
7. The expert collaborative diagnosis system based on rare disease knowledge base according to claim 1, wherein the facility environment in which the expert collaborative diagnosis system operates comprises an application server, a database layer and a base server layer.
8. An expert cooperative diagnosis method based on a rare disease knowledge base is characterized by comprising the following steps:
step 1: generating expert information;
step 2: generating patient information;
and step 3: generating disease knowledge information;
and 4, step 4: generating cooperative hospital information; and
and 5: generating a rare disease collaboration center.
9. An expert cooperative diagnosis device based on a rare disease knowledge base, comprising:
a processor;
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the system or method of any of claims 1-8 via execution of the executable instructions.
10. A computer readable medium storing computer readable instructions, wherein the computer readable instructions, when executed, implement the system or method of any one of claims 1 to 8.
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| CN107658019A (en) * | 2017-11-07 | 2018-02-02 | 池州学院 | A kind of intelligent disease diagnosing system |
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2019
- 2019-12-03 CN CN201911217692.4A patent/CN111028958A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102368283A (en) * | 2011-02-21 | 2012-03-07 | 麦克奥迪实业集团有限公司 | Digital slice-based digital remote pathological diagnosis system and method |
| CN104504488A (en) * | 2014-11-13 | 2015-04-08 | 同心医联科技（北京）有限公司 | System and method for intelligentizing tumor disease management under multidisciplinary collaboration |
| CN107658019A (en) * | 2017-11-07 | 2018-02-02 | 池州学院 | A kind of intelligent disease diagnosing system |
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Application publication date: 20200417 |