Case library construction system

Abstract

The invention provides a case library construction system. The case library construction system comprises a case report module which feeds back patient pathology clinically and arranges the patient pathology into an electronic report; the extraction module is used for summarizing the extraction module to obtain a related information data set module; the classification module is used for generating classification by utilizing a case library system according to the related information data set; the summary module is used for analyzing project results, obtaining project examples mapping practical experience and determining case treatment conditions according to the practical experience; a storage module; and the retrieval module is used for retrieving the cases stored in the pathology knowledge base. The collected case report module is extracted through the extraction module, the analysis module analyzes, classifies and summarizes, the retrieval module is arranged, and medical staff or teaching staff can retrieve conveniently through the retrieval module.

Description

Technical Field

[0001] The present invention relates to the medical field, and in particular to a case library construction system. Background Art

[0002] The current case database on the market is a secure, real-time, patient-centered information resource platform serving doctors. It records daily follow-up patient information into the system anytime and anywhere, automatically organizes it into case documents, and is easy to find and call at any time. It accumulates information throughout life and will never be lost. Its main functions include: case management (input-review); medical history collection; physical examination; auxiliary examination; diagnosis and treatment; doctor-patient communication; skill operation; admission record; case parameter maintenance;

[0003] However, in reality, these case databases are only used as in-hospital systems and are not utilized for teaching. Moreover, many hospitals are teaching hospitals themselves, so there is actually a bit of a waste of resources. Summary of the Invention

[0004] The problem to be solved by the present invention is to provide a case library construction system to facilitate the collection and study of cases in view of the above-mentioned deficiencies in the prior art.

[0005] To achieve the above-mentioned objectives, the present invention adopts the following technical solutions: a case library construction system, including a case report module that collects clinical feedback on patient pathology and organizes it into an electronic report; an extraction module that is configured to perform feature extraction on the data of the case report module and to extract knowledge from the text data using a word segmentation dictionary; a module that summarizes and aggregates the extraction module to obtain a relevant information data set; a classification module that generates classifications using a case library system based on the relevant information data set; a summary module that analyzes project results, obtains project examples that map practical experience, and determines case treatment conditions based on practical experience; a storage module that is configured to store the extracted case features and knowledge in the text to form a pathology knowledge base; and a retrieval module that is used to retrieve cases stored in the pathology knowledge base.

[0006] Furthermore, the classification module includes a sample module, a learning module and a diagnosis module, wherein the sample module is used to obtain a sample library of the patient's specific condition; the learning module is used to record the notes obtained by medical staff during the diagnosis process; and the diagnosis module is a record of the diagnostic method obtained for the patient's specific pathology.

[0007] Furthermore, the extraction module obtains the indicators to be screened and the parameter characteristics corresponding to each indicator to be screened based on the standards for cases to be included in the database, generates a corresponding first data identifier, and generates a data comparison table based on the first data identifier; identifies the preliminary case based on the parameter characteristics, refers to the first data identifier, and adds the corresponding second data identifier to the data in the preliminary case based on the identification result; obtains the second data identifier of each preliminary case, and based on the data comparison table, determines whether the data type of each preliminary case meets the standards. If so, determines whether the data of the preliminary case is complete. When the data of the preliminary case is complete, the preliminary case is determined to be a target case; if not, the preliminary case is determined to be a non-target case.

[0008] Furthermore, the extraction module includes a first extraction module and a second extraction module. The first extraction module extracts and classifies cases for building a pathology knowledge base, and the second extraction module extracts the pathology knowledge base when the retrieval module searches.

[0009] Furthermore, the case library construction system also includes an analysis module, which is used to analyze the case information retrieved by the retrieval module and generate a corresponding atlas, and the analysis module is also connected to the Internet.

[0010] Furthermore, the case library construction system also includes a teaching module, which is connected to the retrieval module via the Internet. The teaching module includes a dot matrix teaching courseware, a dot matrix acquisition device and a teacher terminal; an answer area is provided on the dot matrix teaching courseware, and the answer area is provided with a dot matrix code, and the dot matrix code is used to form answer data for the test question at any position in the answer area; the dot matrix acquisition device is used to collect the answer data for the test question; the teacher terminal is used to obtain the answer data for the test question collected by the dot matrix acquisition device, and determine the matching result between the answer data and the test question.

[0011] Compared with the prior art, the present invention has the following beneficial effects: the present invention extracts the collected case report module through the extraction module, and the analysis module analyzes, classifies and summarizes it, and is equipped with a retrieval module, which facilitates retrieval by medical staff or teaching staff.

[0012] Other advantages, objectives and features of the present invention will be reflected in part through the following description, and in part will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 Schematic diagram of a case library construction system. DETAILED DESCRIPTION

[0014] In order to make the technical means, creative features, objectives and functions of the present invention clearer and easier to understand, the present invention is further described below with reference to the accompanying drawings and specific embodiments:

[0015] The present invention proposes a case library construction system, including a case report module that collects clinical feedback on patient pathology and compiles it into an electronic report; an extraction module that is configured to extract features from the data in the case report module and extract knowledge from the text data using a word segmentation dictionary; a module that summarizes and aggregates the extraction module to obtain a relevant information data set; a classification module that generates classifications using a case library system based on the relevant information data set; a summary module that analyzes project results, obtains project examples that map practical experience, and determines case treatment conditions based on practical experience; a storage module that is configured to store the extracted case features and knowledge in the text to form a pathology knowledge base; a retrieval module that is used to retrieve cases stored in the pathology knowledge base; the case report module includes: a case introduction module, a case demand and research question module, a case key point module, an available resource and constraint module, and a case boundary module; a project boundary module that is used to describe the participant roles for basic needs and case themes, namely, patients and the scope related to their diseases.

[0016] The case library construction system also includes a background module, which includes: a user management module, an interaction module, a case entry module and a system administrator module, wherein: the user management module includes four parts: user role setting, user registration and login, user real-name authentication and user personal center; the user role setting divides user types into four categories: students, users, authenticated users and administrators; wherein, user identities include individuals and teams; students refer to users who have not registered and logged in to the system, and are temporary accounts given to students by users. Students have the right to browse the system homepage, case center, case canvas and other interfaces, but do not have the right to view case details and personal center; students become users by registering and logging in. The user needs to obtain the user's consent. The permissions granted by the user to the administrator are those of a teacher or medical staff in school. The permissions they have include: browsing the system homepage, case center, case canvas, and having a personal center. They can use the two functions of editing personal information and viewing system notifications in the personal center; but they cannot view case details; after the user passes the real-name authentication, he becomes a certified user. The permissions of the certified user include: viewing the system homepage, case center, case canvas, case details and other interfaces and using all functions of the personal center; the administrator has the highest system authority and can review and manage all users and case information; the background module is connected to the case reporting module, extraction module, analysis module, storage module and retrieval module.

[0017] The classification module includes a sample module, a learning module and a diagnosis module, wherein the sample module is used to obtain a sample library of the patient's specific condition; the learning module is used to obtain the notes obtained by medical staff during the diagnosis process; the diagnosis module is a record of the diagnostic method obtained for the patient's specific pathology; the learning module is used to use machine learning methods to determine the correlation between each relevant factor and each diagnosis in the case sample library, and obtain a target correlation directed graph.

[0018] The case report module pre-processes, analyzes, and mines the uploaded data, divides it according to the hierarchical classification standards, extracts the correlation between hierarchical organizations, and extracts medical and pathological keywords to enrich the word segmentation dictionary; since imaging data will be uploaded at the same time after the document data is uploaded, for example, when a case is uploaded, case-related imaging data will be uploaded, and a one-to-many relationship will be established between the two extracted data; text data is structured and distributedly stored, and slices and imaging data are clustered and distributed. File storage and timed snapshot copies are performed to avoid data loss, and are stored by the storage module; feature extraction is performed on images; the correlation between structured data and unstructured data is established to meet the diversified display of knowledge graphs; and finally a related information dataset module is formed.

[0019] The extraction module obtains the indicators to be screened and the parameter characteristics corresponding to each indicator to be screened based on the standards for the cases to be included in the database, generates a corresponding first data identifier, and generates a data comparison table based on the first data identifier; identifies the preliminary case based on the parameter characteristics, refers to the first data identifier, and adds the corresponding second data identifier to the data in the preliminary case based on the identification result; obtains the second data identifier of each preliminary case, and based on the data comparison table, determines whether the data type of each preliminary case meets the standards. If so, determines whether the data of the preliminary case is complete. When the data of the preliminary case is complete, the preliminary case is determined to be a target case; if not, the preliminary case is determined to be a non-target case.

[0020] The extraction module includes a first extraction module and a second extraction module. The first extraction module extracts and classifies cases for building a pathology knowledge base, and the second extraction module extracts the pathology knowledge base when the retrieval module searches.

[0021] The case library construction system also includes an analysis module, which is used to analyze the case information retrieved by the retrieval module and generate a corresponding atlas. The analysis module is also connected to the Internet.

[0022] The case library construction system also includes a teaching module, which is connected to the retrieval module via the Internet. The teaching module includes a dot matrix teaching courseware, a dot matrix acquisition device and a teacher terminal; an answer area is provided on the dot matrix teaching courseware, and the answer area is provided with a dot matrix code, and the dot matrix code is used to form answer data for the test question at any position in the answer area; the dot matrix acquisition device is used to collect the answer data for the test question; the teacher terminal is used to obtain the answer data for the test question collected by the dot matrix acquisition device, and determine the matching result between the answer data and the test question.

[0023] When there is a need for teaching, the target teaching module is generated by the teaching module. The target teaching module has a target teaching file. The specific process of generating the target layout data according to the target teaching file can be: generating the corresponding answer area according to each test question in the target teaching file, for example, generating an objective question answer area according to an objective question, and generating a subjective question answer area according to a subjective question; in order to distinguish between the subjective question answer area and the objective question answer area, a label of the answer area can be generated, for example, the label of the objective question answer area is "0", and the label of the subjective question answer area is "1". Of course, the label of the answer area can also be "a", "b", etc., and this application does not limit this; sorting each answer area according to its corresponding test question number, and according to the sorting, arranging each answer area in turn in the printing area of the target layout data to generate the target layout data; the target teaching module is also matched with the analysis module through the Internet, and systematically analyzes the final teaching results, including scoring.

[0024] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A case library construction system, characterized by: It includes a case report module that collects clinical feedback on patient pathology and compiles it into an electronic report; an extraction module that is configured to extract features from the data in the case report module and extract knowledge from text data using a word segmentation dictionary; and a module that summarizes the extraction module to obtain relevant information datasets. Based on the relevant information dataset, a classification module is generated using the case library system; A summary module used to analyze project results, obtain project examples that map practical experience, and determine case treatment status based on practical experience; The storage module is configured to store the extracted case features and knowledge in the text to form a pathology knowledge base; the retrieval module is used to retrieve the cases stored in the pathology knowledge base.

2. A case library construction system according to claim 1, characterized in that: The classification module includes a sample module, a learning module and a diagnosis module, wherein the sample module is used to obtain a sample library of the patient's specific condition; the learning module is used to record the notes obtained by medical staff during the diagnosis process; and the diagnosis module is a record of the diagnostic method obtained for the patient's specific pathology.

3. The case library construction system according to claim 1, characterized in that: The extraction module obtains the indicators to be screened and the parameter characteristics corresponding to each indicator to be screened based on the criteria for the cases to be included in the database, generates the corresponding first data identifier, and generates a data comparison table according to the first data identifier; Identify the preliminary case according to the parameter characteristics, refer to the first data identifier, and add a corresponding second data identifier to the data in the preliminary case based on the identification result; Obtain the second data identifier of each preliminary case, and based on the data comparison table, determine whether the data type of each preliminary case meets the standard. If so, determine whether the preliminary case data is complete. When the preliminary case data is complete, determine that the preliminary case is a target case; if not, determine that the preliminary case is not a target case.

4. A case library construction system according to claim 3, characterized in that: The extraction module includes a first extraction module and a second extraction module. The first extraction module extracts and classifies cases for building a pathology knowledge base, and the second extraction module extracts the pathology knowledge base when the retrieval module searches.

5. The case library construction system according to claim 1, characterized in that: The case library construction system also includes an analysis module, which is used to analyze the case information retrieved by the retrieval module and generate a corresponding atlas. The analysis module is also connected to the Internet.

6. A case library construction system according to claim 5, characterized in that: The case library construction system further includes a teaching module, the teaching module being connected to the retrieval module via the Internet, the teaching module including a dot matrix teaching courseware, a dot matrix acquisition device, and a teacher terminal; an answer area is provided on the dot matrix teaching courseware, the answer area being provided with a dot matrix code, the dot matrix code being used to form answer data for a test question at any position in the answer area; The dot matrix acquisition device is used to collect the answer data for the test question; The teacher terminal is used to obtain the answer data for the test question collected by the dot matrix acquisition device, and determine the matching result between the answer data and the test question.

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