Medical record data processing method, apparatus, computer device and storage medium

Abstract

The present application relates to a machine learning technology in the field of artificial intelligence and provides a medical record data processing method, a medical record data processing apparatus, a computer device and a storage medium. The method includes the following steps that: feature words are extracted from source medical records, so that a feature word set is obtained, wherein the feature word set includes identity feature words and pathological feature words; and the matching degree of the feature word set and a feature word set corresponding to historical medical records in a historical medical record set is calculated, reference medical records are selected according to calculation results, and a reference medical record set is obtained; a trained classification model is used to obtain the patient categories of patients corresponding to the source medical records according to the identity feature words; screening factors corresponding to the patient categories are obtained, and the reference medical records in the reference medical record set are sequenced according to the screening factors, and a first predetermined number of reference medical records are selectedas target reference medical records according to the sequencing results of the reference medical records; and the target reference medical records are sent to doctor terminals. With the method adopted, the efficiency and accuracy of clinical assistant decision-making can be improved.

Description

Technical field [0001] This application relates to the field of computer application technology, in particular to a medical record data processing method, device, computer equipment and storage medium. Background technique [0002] With the development of computer application technology, clinical aid decision-making based on computers has been increasingly used in the medical field. [0003] At present, clinical decision-making systems are mostly implemented with the help of huge medical knowledge bases and complicated medical rules. However, the diagnosis and treatment plans pushed by clinical decision-making assistance are difficult to predict the final treatment results, lack of real data verification, and lack of reference for doctors to choose. , Can only be judged based on own experience, not only is inefficient, but also because of the different experience and educational background of each doctor, the overall accuracy is not high. Summary of the invention [0004] Based on ...

AI Technical Summary

Problems solved by technology

[0003] At present, clinical auxiliary decision-making systems are mostly implemented with the help of a huge medical knowledge base and complicated medical rules. However, due to the diagnosis and treatment plan pushed by clinical auxiliary decision-making, it is difficult to predict the final treatment result, lack of real data verification, and lack of reference for doctors to choose , can only be judged based on one's own experience, which is not only inefficient, but also the overall accuracy is not high due to the differences in the experience and academic qualifications of each doctor

Images