CN113936756A - Clinical test scoring system for tumors - Google Patents
Clinical test scoring system for tumors Download PDFInfo
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- CN113936756A CN113936756A CN202111070050.3A CN202111070050A CN113936756A CN 113936756 A CN113936756 A CN 113936756A CN 202111070050 A CN202111070050 A CN 202111070050A CN 113936756 A CN113936756 A CN 113936756A
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- 238000012360 testing method Methods 0.000 title claims abstract description 77
- 206010028980 Neoplasm Diseases 0.000 title claims abstract description 21
- 238000011282 treatment Methods 0.000 claims abstract description 31
- 201000010099 disease Diseases 0.000 claims abstract description 29
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 29
- 238000011156 evaluation Methods 0.000 claims abstract description 21
- 238000003745 diagnosis Methods 0.000 claims abstract description 19
- 230000003993 interaction Effects 0.000 claims description 21
- 230000036541 health Effects 0.000 claims description 10
- 239000003814 drug Substances 0.000 claims description 8
- 229940079593 drug Drugs 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 3
- 230000002035 prolonged effect Effects 0.000 abstract description 3
- 230000004083 survival effect Effects 0.000 abstract description 3
- 239000002547 new drug Substances 0.000 abstract 1
- 238000002474 experimental method Methods 0.000 description 5
- 238000001647 drug administration Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 206010059866 Drug resistance Diseases 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007717 exclusion Effects 0.000 description 1
- 230000029142 excretion Effects 0.000 description 1
- 238000011866 long-term treatment Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000001575 pathological effect Effects 0.000 description 1
- 230000007115 recruitment Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
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- G—PHYSICS
- 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
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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- G—PHYSICS
- 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
- G16H70/00—ICT specially adapted for the handling or processing of medical references
- G16H70/40—ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
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Abstract
The invention discloses a tumor clinical test scoring system in the technical field of tumor clinical test scoring systems, wherein a disease condition evaluation and prediction module is electrically input and connected with a knowledge database, the disease condition evaluation and prediction module is electrically output and connected with a patient test combination grouping module, the patient test combination grouping module is electrically output and connected with a test combination scoring module, the test combination scoring module is electrically input and connected with a scoring classification standard library, the test combination scoring module is electrically output and connected with a test combination score summing module, deep analysis and identification are carried out on specific case conditions, different diagnosis and treatment schemes are determined, then different diagnosis and treatment schemes are scored, the accuracy of clinical patient disease condition identification is greatly improved, the optimized diagnosis and treatment suggestion treatment scheme can be determined in time, more new drugs are used, and the survival time of tumors is prolonged, meanwhile, more clinical trials can be recruited to patients, and win-win situation between patients and sponsors is achieved.
Description
Technical Field
The invention relates to the technical field of a scoring system for clinical tests of tumors, in particular to a scoring system for clinical tests of tumors.
Background
The clinical trial of tumor has huge demand for recruiting patients, the situation that the experiment can not be completed due to insufficient recruited patients exists, patients with late tumor have no medicine available after drug resistance, the treatment can be obtained only by registering and participating in clinical trials, the entry and discharge conditions of each clinical trial relate to the situation of mutual exclusion, the disease condition progresses after the clinical trials are out of groups, the clinical trials are registered and participated, the participated clinical trials are less and less, in the prior art scheme, the patient information is mainly collected, the structured data is carried out and then matched with the entry and discharge data of the experiment, after the experiment is screened out, the doctor recommends the patient, only the relevant experiment that the patient can currently participate in the condition can be matched according to the disease condition and the entry and discharge of the patient, but the doctor can not make a long-term treatment plan for the patient (the combination among the experiments can not be calculated artificially, the entry and discharge conditions of hundreds of thousands of relevant clinical trials in the field of the department need to be known, the patient can not be treated in the field for a long time, End of recruitment, etc.), to this end we propose a tumor clinical trial scoring system.
Disclosure of Invention
The invention aims to provide a tumor clinical trial scoring system to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides a tumour clinical trial system of grading, includes human-computer interaction input module, human-computer interaction input module electric output connects the state of an illness aassessment prediction module, state of an illness aassessment prediction module electric input connection knowledge database, state of an illness aassessment prediction module electric output connection patient test combination grouping module, patient test combination grouping module electric output connection test combination module of grading, test combination module of grading electric input connection is graded the standard library, test combination module of grading electric output connection test combination score sums up the module.
Preferably, the disease condition evaluation and prediction module evaluates and predicts the grade degree of the health condition according to the physiological parameters and the disease condition information, so that the health condition is evaluated based on the knowledge graph in the knowledge database and is divided into A, B, C, D types, and then the disease onset risk evaluation is performed according to the risk evaluation table, so that the grading processing is performed on each grade conveniently.
Preferably, the patient test combination grouping module performs ranking according to the current illness state of the patient and all tests, and different test combinations are obtained through matching.
Preferably, a dosing scheme database is arranged in the grading and classifying standard library, a grading and classifying table is arranged in the dosing scheme database, as shown in fig. 2, and the test combination grading module is used for receiving the dosing scheme, the treatment mode and the grading rules in the grading and classifying standard library.
Preferably, the test combination score summing module performs ranking processing on the diagnosis and treatment technical scheme and the scheme score sum in the test combination scoring module to obtain the optimized test combination diagnosis and treatment technical scheme under different emphasis points.
Preferably, the human-computer interaction input module comprises a human-computer interaction screen, a wireless transmission module is arranged in the human-computer interaction screen, and a plurality of groups of connection ports are arranged on the human-computer interaction screen.
Compared with the prior art, the invention has the beneficial effects that:
the invention relates to a human-computer interaction input module for completing the input of basic information of a patient, a disease condition evaluation and prediction module evaluates and predicts the grade degree of a health condition according to physiological parameters and disease condition information, so that the health condition is evaluated based on a knowledge graph in a knowledge database, then the disease risk evaluation is carried out according to a risk evaluation table, each grade is conveniently graded, a patient test combination grouping module arranges according to the current disease condition of the patient and all tests and matches to obtain different test combinations, a test combination grading module is used for receiving a medication scheme, a treatment mode and grading detailed rules in a grading classification standard library, a test combination score summing module sequences the patients based on a diagnosis and treatment technical scheme and a grading scheme sum in the test combination grading module to obtain the optimized test combination diagnosis and treatment technical scheme under different side points, the patient can take part in more clinical tests, deep analysis and identification are carried out on specific case conditions, different diagnosis and treatment schemes are determined, then grading treatment is carried out on the different diagnosis and treatment schemes, the accuracy of disease condition identification of the clinical patient is greatly improved, the optimized diagnosis and treatment recommended treatment scheme can be determined in time, more new medicines are used, the tumor survival time is prolonged, meanwhile, more clinical tests can recruit the patient, and the win-win situation of the patient and a sponsor is realized.
Drawings
FIG. 1 is a block diagram of the working principle of the present invention;
FIG. 2 is a diagram of the scoring classification table according to the present invention.
In the figure: 1. a human-computer interaction input module; 2. a disease condition evaluation prediction module; 3. a knowledge database; 4. a patient trial combination grouping module; 5. a test combination scoring module; 6. a score classification standard library; 7. and a test combination score summing module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1 and fig. 2, the present invention provides a technical solution: a clinical tumor test scoring system comprises a human-computer interaction input module 1, wherein the human-computer interaction input module 1 is electrically connected with an illness state evaluation and prediction module 2 in an output mode, the illness state evaluation and prediction module 2 is electrically connected with a knowledge database 3 in an input mode, the illness state evaluation and prediction module 2 is electrically connected with a patient test combination grouping module 4 in an output mode, the patient test combination grouping module 4 is electrically connected with a test combination scoring module 5 in an output mode, the test combination scoring module 5 is electrically connected with a scoring classification standard database 6 in an input mode, and the test combination scoring module 5 is electrically connected with a test combination score summing module 7 in an output mode.
The disease condition evaluation and prediction module 2 evaluates and predicts the grade degree of the health condition according to the physiological parameters and the disease condition information, so that the health condition is evaluated based on the knowledge graph in the knowledge database 3 and is divided into A, B, C, D types, and then the disease risk evaluation is carried out according to the risk evaluation table, so that the grading processing is conveniently carried out on each grade, and the mastery degree of the pathological information of the patient is improved;
the patient test combination grouping module 4 performs entry and discharge according to the current illness state and all tests of the patient, and different test combinations are obtained through matching;
a drug administration scheme database is arranged in the grading classification standard database 6, a grading classification table is arranged in the drug administration scheme database, which is shown in figure 2, and the test combination grading module 5 is used for receiving the drug administration scheme, the treatment mode and the grading detailed rule in the grading classification standard database 6;
the test combination score summing module 7 sequences the diagnosis and treatment technical schemes and the scheme score sums in the test combination scoring module 5 to obtain optimized test combination diagnosis and treatment technical schemes under different emphasis points;
the human-computer interaction input module 1 comprises a human-computer interaction screen, a wireless transmission module is arranged in the human-computer interaction screen, and a plurality of groups of connection ports are arranged on the human-computer interaction screen;
principle of operation
And (3) test combination: performing excretion according to the current disease condition of the patient and all tests, and matching to obtain a related test A;
1, supposing that the patient participates in a test Aa, matching the current state of illness and the medication history of the patient in the later state of illness with the rest tests except Aa to obtain a related test B;
2, supposing that the patient participates in the test Ba, matching the disease condition and the medication history of the patient in two disease condition stages after the current disease condition with the input and output of the rest tests except for the Aa and the Ba to obtain a related test C;
3, obtaining all test combinations An + Bn + Cn of the patients;
test combination scoring: according to the self-research algorithm, A, B, C files set weights according to the tags, see FIG. 2;
wherein, each grade separately calculates the total weight to be used as each grade score of the clinical trial combination;
the scores of the clinical trial combinations can be ranked according to two ways: combining the scoring total ABC three-gear addition descending order and the priority descending order of the current scheme, wherein the first ordering A gear is descending order, the second ordering B gear is descending order, and the third ordering C gear is descending order; for example, if the grades of the A gears of different combinations are the same, comparing the B gears, and if the grades of the B gears are the same, comparing the C gears;
the invention relates to a human-computer interaction input module 1 for completing the input of basic information of a patient, a disease condition evaluation and prediction module 2 for evaluating and predicting the grade degree of a health condition according to physiological parameters and disease condition information, so that the health condition is evaluated based on a knowledge graph in a knowledge database 3, then, the disease risk evaluation is carried out according to a risk evaluation table, each grade is conveniently graded, a patient test combination grouping module 4 is arranged according to the current disease condition and all tests of the patient and matched to obtain different test combinations, a test combination grading module 5 is used for receiving a medication scheme, a treatment mode and grading detailed rules in a grading classification standard library 6, a test combination score summing module 7 is used for carrying out sequencing treatment on the patient based on a diagnosis and treatment technical scheme and a scheme grading sum in the test combination grading module 5 to obtain the optimized test combination diagnosis and treatment technical scheme under different side points, the patient can take part in more clinical tests, deep analysis and identification are carried out on specific case conditions, different diagnosis and treatment schemes are determined, then grading treatment is carried out on the different diagnosis and treatment schemes, the accuracy of disease condition identification of the clinical patient is greatly improved, the optimized diagnosis and treatment recommended treatment scheme can be determined in time, more new medicines are used, the tumor survival time is prolonged, meanwhile, more clinical tests can recruit the patient, and the win-win situation of the patient and a sponsor is realized.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. A clinical trial scoring system for tumors, comprising: including human-computer interaction input module (1), human-computer interaction input module (1) electrical output connects state of an illness aassessment prediction module (2), state of an illness aassessment prediction module (2) electrical input connects knowledge database (3), state of an illness aassessment prediction module (2) electrical output connects patient's experimental combination and divides module (4), patient's experimental combination divides module (4) electrical output connection experimental combination to divide module (5), experimental combination divides module (5) electrical input connection classification standard library (6) of grading, experimental combination divides module (5) electrical output connection experimental combination score to add up module (7).
2. A clinical trial scoring system for tumors as claimed in claim 1, wherein: the disease condition evaluation and prediction module (2) evaluates and predicts the grade degree of the health condition according to the physiological parameters and the disease condition information, so that the health condition is evaluated based on the knowledge graph in the knowledge database (3) and is divided into A, B, C, D types, and then the disease risk evaluation is carried out according to the risk evaluation table, so that the grading processing is conveniently carried out on each grade.
3. A clinical trial scoring system for tumors as claimed in claim 1, wherein: the patient test combination grouping module (4) performs classification according to the current illness state of the patient and all tests, and different test combinations are obtained through matching.
4. A clinical trial scoring system for tumors as claimed in claim 1, wherein: the scoring classification standard library (6) is internally provided with a dosing scheme database, the dosing scheme database is internally provided with a scoring classification table, which is shown in figure 2, and the test combination scoring module (5) is used for receiving the medication scheme, the treatment mode and the scoring rules in the scoring classification standard library (6).
5. A clinical trial scoring system for tumors as claimed in claim 4, wherein: the test combination score summing module (7) sequences the diagnosis and treatment technical schemes and the scheme score sums in the test combination scoring module (5) to obtain the optimized test combination diagnosis and treatment technical schemes under different emphasis points.
6. A clinical trial scoring system for tumors as claimed in claim 1, wherein: the human-computer interaction input module (1) comprises a human-computer interaction screen, a wireless transmission module is arranged in the human-computer interaction screen, and a plurality of groups of connection ports are arranged on the human-computer interaction screen.
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| CN202111070050.3A CN113936756A (en) | 2021-09-13 | 2021-09-13 | Clinical test scoring system for tumors |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114242264A (en) * | 2022-02-24 | 2022-03-25 | 浙江太美医疗科技股份有限公司 | Recommendation scheme display and generation method and device, computer equipment and storage medium |
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|---|---|---|---|---|
| CN1252877A (en) * | 1997-03-13 | 2000-05-10 | 第一咨询公司 | Disease management system |
| US20140316793A1 (en) * | 2013-03-14 | 2014-10-23 | nPruv, Inc. | Systems and methods for recruiting and matching patients for clinical trials |
| US20200243168A1 (en) * | 2019-01-29 | 2020-07-30 | International Business Machines Corporation | Intelligent ranking of clinical trials for a patient |
| CN111667891A (en) * | 2020-06-08 | 2020-09-15 | 中国医学科学院医学信息研究所 | Queue identification method and device applied to clinical test of special diseases |
| US20200411199A1 (en) * | 2018-01-22 | 2020-12-31 | Cancer Commons | Platforms for conducting virtual trials |
| CN113228195A (en) * | 2019-01-15 | 2021-08-06 | 国际商业机器公司 | Techniques for identifying optimal combinations of drugs |
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2021
- 2021-09-13 CN CN202111070050.3A patent/CN113936756A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1252877A (en) * | 1997-03-13 | 2000-05-10 | 第一咨询公司 | Disease management system |
| US20140316793A1 (en) * | 2013-03-14 | 2014-10-23 | nPruv, Inc. | Systems and methods for recruiting and matching patients for clinical trials |
| US20200411199A1 (en) * | 2018-01-22 | 2020-12-31 | Cancer Commons | Platforms for conducting virtual trials |
| CN113228195A (en) * | 2019-01-15 | 2021-08-06 | 国际商业机器公司 | Techniques for identifying optimal combinations of drugs |
| US20200243168A1 (en) * | 2019-01-29 | 2020-07-30 | International Business Machines Corporation | Intelligent ranking of clinical trials for a patient |
| CN111667891A (en) * | 2020-06-08 | 2020-09-15 | 中国医学科学院医学信息研究所 | Queue identification method and device applied to clinical test of special diseases |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114242264A (en) * | 2022-02-24 | 2022-03-25 | 浙江太美医疗科技股份有限公司 | Recommendation scheme display and generation method and device, computer equipment and storage medium |
| CN114242264B (en) * | 2022-02-24 | 2022-08-02 | 浙江太美医疗科技股份有限公司 | Recommendation scheme display and generation method and device, computer equipment and storage medium |
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