Clinical test subject recruitment intelligent item matching system

Abstract

The invention discloses a clinical test subject recruitment intelligent item matching system, which comprises a recruitment end, a collection end and an information processing platform, and is characterized in that the recruitment end and the collection end are respectively used as input ends to store information in the information processing platform; the information processing platform comprises an acquired data classification pre-storage unit, a classification conversion scoring unit, a comparison unit, a standard data storage unit and a subject invitation unit. The invention belongs to the technical field of data conversion and comparison, and particularly relates to an intelligent item matching system for clinical test subject recruitment, which is used for simplifying subject data information aiming at subject recruitment of a clinical test, converting subject information numerical values, comparing the subject information numerical values with standard data of a recruitment end and simplifying a matching process.

Description

Technical Field

[0001] The present invention belongs to the technical field of data conversion and comparison, and in particular to an intelligent project matching system for recruiting clinical trial subjects. Background Art

[0002] Clinical trial refers to any systematic study of a drug on humans to confirm or reveal the effects, adverse reactions, or absorption, distribution, metabolism, and excretion of the trial drug, with the goal of determining the efficacy and safety of the trial drug.

[0003] Currently, clinical trial recruitment of subjects is mainly done manually by screening matching subjects based on their medical records, examination reports, etc., or by collecting information such as subjects' medical records and examination reports to establish a subject database, and automatically matching suitable subjects in the subject database through big data.

[0004] The amount of data information on the subjects is large and cannot be classified according to the specific circumstances of the subjects. Moreover, the transformation of the classified subject information cannot be intuitively compared with the standard data, making it impossible to directly screen out the subjects who match the recruitment project, thereby increasing the difficulty of matching. Summary of the invention

[0005] The technical problem to be solved by the present invention is to simplify the subject data information, perform numerical conversion processing on the subject information, compare it with the standard data of the recruitment end, and simplify the matching process.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows: a clinical trial subject recruitment intelligent project matching system, comprising a recruitment end, a collection end and an information processing platform, wherein the recruitment end and the collection end respectively serve as input ends to store information in the information processing platform;

[0007] The information processing platform includes a collection data classification pre-storage unit, a classification conversion scoring unit, a comparison unit, a standard data storage unit and a subject invitation unit;

[0008] The acquisition end acquires data according to the medical information of the subject through the acquisition data classification pre-storage unit, performs project classification and preliminary screening;

[0009] The recruitment end establishes a standard database according to the test conditions of the clinical trial through a standard data storage unit;

[0010] The classification-to-scoring unit performs data conversion on the medical information of the subject and performs rescreening and comparison on the basic items;

[0011] The comparison unit compares the subject information after rescreening and comparison with the standard data storage unit, and selects and stores it in the reserve library using the staged scoring, and transmits the comparison result of the comparison unit to the subject at the collection end, and at the same time sends the subject information that meets the recruitment project to the recruitment end;

[0012] A reserve library is connected between the comparison unit and the recruitment end, and the subject invitation unit is connected to the comparison unit and connected between the recruitment end and the collection end. After the comparison meets the recruitment project conditions, invitation information is sent to the recruitment end and the collection end.

[0013] Furthermore, the standard database is a clinical project classification library, through which the recruitment projects are classified and scoring standards are established, which are stored in the sub-database.

[0014] Furthermore, the acquisition end includes an image module and a text module, and the image module uploads the subject information through medical images and photos;

[0015] The text module uses text to upload and record cases, complications and names of drugs used, and can also upload according to the subject's self-report.

[0016] Furthermore, the collected data classification pre-storage unit extracts key pixels and keyword groups based on the images and text information uploaded by the subjects, and classifies and stores the subjects according to clinical medical categories. The collected data classification pre-storage unit is connected to a pre-storage library, and stores the acquired information in the pre-storage library.

[0017] Furthermore, the collected data classification pre-storage unit confirms the specific test items of the subject according to the information filled in by the collection end, confirms the specific clinical causes to exclude, and conducts preliminary screening of the subject to determine whether it meets the recruitment standards.

[0018] Furthermore, the classification conversion scoring unit converts the stored information of the pre-storage library into a scoring conversion, converts it into a phased value by comparing it with the information of the sub-database, and evaluates the information conversion of the subject.

[0019] Furthermore, the classification conversion scoring unit compares the information with the sub-database through image pixels and keyword groups.

[0020] Furthermore, the comparison unit compares the value of the classification conversion scoring unit with the value of the standard data storage unit, and uses the comparison unit to send information to the recruitment end and the collection end according to the difference in the value comparison.

[0021] After adopting the above structure, the beneficial effects of the present invention are as follows: for the recruitment of subjects for clinical trials, the conditions of different subjects are recorded through the information processing platform, and stored according to the clinical medical display classification, the standard data storage unit established at the recruitment end is used as the data benchmark, the classified storage data at the collection end is converted into a score close to the standard data through the classification conversion scoring unit, and a simple data comparison is implemented between the standard data storage unit and the classification conversion scoring unit using a comparison module to achieve screening, so that different test items are matched with the subject information with the highest conversion score, the classification of subject information is simplified, and the subject conditions are improved by making the subject information score close to the standard of the test item, so that the subject information and the test item are intelligently matched. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0023] Figure 1 This is the overall flow chart of the intelligent project matching system for clinical trial subject recruitment proposed by the present invention;

[0024] Figure 2 This is a flow chart of the collection end of the intelligent project matching system for clinical trial subject recruitment proposed by the present invention;

[0025] Figure 3 This is a flow chart of the collected data classification and pre-storage module of the clinical trial subject recruitment intelligent project matching system proposed by the present invention;

[0026] Figure 4 This is a flow chart of a standard data storage unit of the intelligent project matching system for clinical trial subject recruitment proposed by the present invention.

[0027] In the attached drawings: 1. Recruitment end, 2. Collection end, 3. Information processing platform, 4. Collection data classification pre-storage unit, 5. Classification conversion scoring unit, 6. Comparison unit, 7. Standard data storage unit, 8. Subject invitation unit, 9. Standard database, 10. Reserve library, 11. Sub-database, 12. Image module, 13. Text module, 14. Pre-storage library. DETAILED DESCRIPTION

[0028] like Figure 1As shown, the intelligent project matching system for recruiting clinical trial subjects includes a recruitment terminal 1, a collection terminal 2 and an information processing platform 3. The recruitment terminal 1 and the collection terminal 2 respectively serve as input terminals to store information in the information processing platform 3. The recruitment terminal 1 and the collection terminal 2 respectively transmit information to the information processing platform 3. The information processing platform 3 is used to classify, transform and compare the information of the recruitment terminal 1 and the collection terminal 2. The information processing platform 3 includes a collection data classification pre-storage unit 4, a classification conversion scoring unit 5, a comparison unit 6, a standard data storage unit 7 and a subject invitation unit 8.

[0029] like Figure 4 As shown, in order to realize the screening, judgment and comparison of subject information, the recruitment end 1 establishes a standard database 9 through the standard data storage unit 7 according to the subject conditions of the clinical trial, establishes standards through the display of clinical medical symptoms in the form of pictures and texts, and converts the standard data into scores, so that the reference value of the standard data is 1, and the established standard value is stored in the standard database 9, which is used for the initial screening, subject information conversion and score comparison after the subject is collected and classified and stored. The standard database 9 is a clinical project classification library, which classifies the recruitment projects and establishes scoring standards through the clinical project classification library, and stores them in the sub-database 11.

[0030] like Figure 2 and Figure 3 As shown, in order to improve the data accuracy of the acquisition terminal 2, facilitate the conversion of the score of the subject information, and perform a preliminary screening of the subject information, the acquisition terminal 2 is used to obtain data according to the medical information of the subject through the acquisition data classification pre-storage unit 4, and classify and pre-screen the items. The acquisition terminal 2 includes an image module 12 and a text module 13. The image module 12 uploads the subject information through medical images and photos, and uploads the subject's picture information to the platform in the form of images such as medical images or photos. In combination with the text module 13, the case, complication and the name of the drug used are uploaded and recorded in text form. At the same time, it can also be uploaded according to the subject's self-report to increase the amount of subject information. The uploaded graphic and text information is compared with the information in the standard database 9. According to the information uploaded by the subject and combined with the category of clinical medicine, the cause of the disease is preliminarily screened and classified and stored to determine whether the subject meets the recruitment project. The acquisition data classification pre-storage unit 4 confirms the specific test item of the subject according to the information filled in by the acquisition terminal 2, and confirms the specific clinical cause to exclude it. Whether it meets the recruitment standards, the subject is preliminarily screened.

[0031] like Figure 1As shown, in order to simplify the matching process, the classified and stored subject information is converted, the classification-to-scoring unit performs data conversion on the medical information of the subject, re-screens and compares the basic items, extracts the classified subject information, and compares it with the standard data in the standard database 9, and the acquisition data classification pre-storage unit 4 extracts key pixels and keyword groups based on the images and text information uploaded by the subject, and stores the subjects according to the clinical medicine categories. The acquisition data classification pre-storage unit 4 is connected to the pre-storage library 14, and the acquired information is stored in the pre-storage library 14. According to the project classification, the subject information can be scored by combining the pixel overlap of the medical image and the keyword groups in the text description to obtain a reference value close to the standard data.

[0032] like Figure 1 As shown, in order to improve the conditions of the subjects and make the subject information match the test items intelligently, the comparison unit 6 compares the subject information after rescreening and comparison with the standard data storage unit 7, and uses the phased scoring to select and store it in the reserve library 10, and transmits it to the subjects of the collection end 2 according to the comparison result of the comparison unit 6, and at the same time, the subject information that meets the recruitment project is sent to the recruitment end 1, and the value converted by the classification conversion scoring unit 5 is compared with the reference value of the standard data, the subject data is rescreened and scored, and phased storage selection is performed according to the score. The reserve library 10 is connected between the comparison unit 6 and the recruitment end 1, and the subject invitation unit 8 is connected to the comparison unit 6 and connected between the recruitment end 1 and the collection end 2. After the comparison, if it meets the conditions of the recruitment project, the invitation information is sent to the recruitment end 1 and the collection end 2.

[0033] When used specifically, the recruitment terminal 1 and the collection terminal 2 transmit information to the information processing platform 3 respectively, and a clinical project classification library is established through the recruitment terminal 1, and scoring standards for different projects are established through the clinical project classification library and stored in the sub-database 11;

[0034] Collect the subject information by means of APP or other methods, compare the uploaded text and picture information with the standard database 9 by means of pictures and texts, preliminarily screen the cause of disease according to the information uploaded by the subject and the category of clinical medicine, and store it in the pre-storage library 14 by category, and judge whether the subject meets the recruitment project, confirm the specific test project of the subject according to the information filled in by the collection terminal 2, confirm the specific clinical cause of disease to exclude, and preliminarily screen the subject to see whether it meets the recruitment standard;

[0035] The collected and stored subject information is classified and converted. According to the project classification, the subject information can be scored by combining the pixel overlap of the medical image and the key words in the text description to obtain a reference value close to the standard data. The value converted by the classification conversion scoring unit 5 is compared with the reference value of the standard data, the subject data score is re-screened, and the reserve pool 10 is reserved based on the score. After comparison, if the subjects meet the conditions of the recruitment project, the subjects who meet the recruitment conditions send invitation information to the recruitment end 1 and the collection end 2 through the information processing platform 3 to communicate the test conditions and the reward mechanism. The subjects who do not meet the recruitment conditions feedback information to the collection end 2 to inform the subjects. The classification of the subject information is simplified, and the subject information score is close to the standard of the test project, the subject conditions are improved, and the subject information and the test project are intelligently matched.

[0036] Although the embodiments of the present invention have been shown and described, it is understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents. In short, if those skilled in the art are inspired by them and design structural modes and embodiments similar to the technical solution without creativity without departing from the purpose of the present invention, they shall all fall within the scope of protection of the present invention.

Claims

1. Intelligent project matching system for clinical trial subject recruitment, characterized by: It includes a recruitment end, a collection end and an information processing platform, wherein the recruitment end and the collection end respectively serve as input ends to store information in the information processing platform; The information processing platform includes a collection data classification pre-storage unit, a classification conversion scoring unit, a comparison unit, a standard data storage unit and a subject invitation unit; The acquisition end acquires data according to the medical information of the subject through the acquisition data classification pre-storage unit, performs project classification and preliminary screening; The recruitment end establishes a standard database according to the test conditions of the clinical trial through a standard data storage unit; The classification-to-scoring unit performs data conversion on the medical information of the subject and performs rescreening and comparison on the basic items; The comparison unit compares the subject information after rescreening and comparison with the standard database of the standard data storage unit, and selects to store in the reserve library by using the staged scoring, and transmits the comparison result of the comparison unit to the subject at the collection end, and at the same time sends the subject information that meets the recruitment project to the recruitment end; A reserve library is connected between the comparison unit and the recruitment end, and the subject invitation unit is connected to the comparison unit and connected between the recruitment end and the collection end. After the comparison meets the recruitment project conditions, invitation information is sent to the recruitment end and the collection end.

2. The clinical trial subject recruitment intelligent project matching system according to claim 1, characterized in that: The standard database is a clinical project classification library, through which recruitment projects are classified and scoring standards are established, which are stored in the sub-database.

3. The clinical trial subject recruitment intelligent project matching system according to claim 1, characterized in that: The acquisition end includes an image module and a text module, and the image module uploads the subject information through medical images and photos; The text module uses text to upload and record the case, complications and the names of the drugs used, and also uploads the subject's self-report.

4. The clinical trial subject recruitment intelligent project matching system according to claim 3, characterized in that: The collected data classification pre-storage unit extracts key pixels and keyword groups based on the images and text information uploaded by the subjects, and classifies and stores the subjects according to clinical medical categories. The collected data classification pre-storage unit is connected to a pre-storage library, and stores the acquired information in the pre-storage library.

5. The clinical trial subject recruitment intelligent project matching system according to claim 3 or 4, characterized in that: The collected data classification pre-storage unit confirms the specific test items of the subject according to the information filled in by the collection end, confirms the specific clinical causes to exclude, and conducts preliminary screening of the subject to determine whether it meets the recruitment standards.

6. The clinical trial subject recruitment intelligent project matching system according to claim 3, characterized in that: The classification conversion scoring unit converts the stored information in the pre-storage library into a scoring value by comparing it with the information in the sub-database, and evaluates the information conversion of the subject.

7. The clinical trial subject recruitment intelligent project matching system according to claim 6, characterized in that: The classification conversion scoring unit compares the information with the sub-database through image pixels and keyword groups.

8. The clinical trial subject recruitment intelligent project matching system according to claim 1, characterized in that: The comparison unit compares the value of the classification conversion scoring unit with the value of the standard data storage unit, and uses the comparison unit to send information to the recruitment end and the collection end according to the difference in the value comparison.

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