Diabetic complications analysis method and device
An analysis method and complication technology, applied in medical data mining, medical informatics, computer-aided medical procedures, etc., can solve the problems of the accuracy and complexity of complications, and achieve the effect of improving the accuracy of diagnosis and treatment
Active Publication Date: 2021-10-22
HEFEI UNIV OF TECH
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Traditional disease discovery mainly includes association rule discovery, classification analysis, and cluster analysis, etc., and is mainly based on structured data. However, medical information data is mostly stored in the information system of medical institutions in the form of Html text, which requires complex data structuring work
In addition, the characteristic attributes of different diseases are complex and diverse, and the data after structured processing also contains a lot of noise, which is likely to have a major impact on the accuracy of complication detection
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[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0049] At present, after a long period of development and research, disease detection methods have become an important research direction in medical data mining and other fields. Traditional disease discovery mainly includes association rule discovery, classification analysis, and cluster analysis, etc., and is mainly based on structured data. However, medical information data is mostly stored in the information system of medical institutions in the form of XML...
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The invention provides a method and device for analyzing diabetic complications. The method includes: acquiring a medical record document set; the medical record document set includes a first number of medical record documents; each medical record document includes at least one medical course record; acquiring the medical course record-subject distribution of the at least one medical course record, and obtaining each The disease course record vector of the medical record document; the classification label of the disease course record vector is obtained; the disease discovery model is trained by using multiple classification labels of each medical record record to obtain the final disease discovery model. It can be seen that the present invention can use the actual disease evolution in the course records to detect complications not found in the admission diagnosis, which is conducive to improving the accuracy of diagnosis and treatment of subsequent patients.
Description
technical field [0001] The invention relates to the technical field of data mining, in particular to a method and device for analyzing diabetic complications. Background technique [0002] When a patient is admitted to the hospital, the doctor will make an admission diagnosis, and will issue a treatment plan based on the admission diagnosis in the follow-up diagnosis and treatment process, so as to better solve the patient's suffering. Therefore, admission diagnosis is a very important task, and one of the key points is disease discovery . [0003] At present, after a long period of development and research, disease detection methods have become an important research direction in medical data mining and other fields. Traditional disease discovery mainly includes association rule discovery, classification analysis, and cluster analysis, etc., and is mainly based on structured data. However, medical information data is mostly stored in the information system of medical instit...
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IPC IPC(8): G16H50/70
CPCG16H50/70
Inventor 丁帅杨善林金行俞尧
Owner HEFEI UNIV OF TECH