Multi-population collaborative entropy cascading method for electronic medical record knowledge reduction performance evaluation

Abstract

The invention discloses a multi-population collaborative entropy cascading method for electronic medical record knowledge reduction performance evaluation. The method includes: dividing a large-scale electronic medical record data set into different electronic medical record optimized data subsets by using a Map operation and a Reduce operation in cloud computing; constructing a neighbouring evolution population similarity matrix, and designing a knowledge reduction performance computing method by using an evolution population collaborative entropy; analyzing an evolution population distribution law affecting the electronic medical record knowledge reduction performance, and constructing a cascading evaluation index matrix and performing matrix optimization; and finally evaluating the electronic medical record knowledge reduction performance evaluation precision, and outputting the electronic medical record knowledge reduction performance optimal evaluation precision. The method has good application value in large-scale electronic medical record knowledge reduction qualitative quantitative intelligent analysis and relevant disease auxiliary diagnosis effect evaluation.

Description

Technical field: [0001] The invention relates to the field of intelligent processing of medical information, in particular to a multi-group cooperative entropy cascading method for evaluating the efficiency of knowledge reduction of electronic medical records. Background technique: [0002] With the advent of the era of cloud computing and big data, the processing mechanism of large-scale electronic medical records is extremely complicated in the process of generating and using big medical and health data. High value features, the large-scale electronic medical record system contains valuable medical rules and knowledge, which has become the driving force for people to process electronic medical record data, and the effectiveness evaluation of electronic medical record knowledge reduction is the key to forming a clinical decision support system, using some efficient methods Carrying out the efficiency analysis of knowledge reduction in complex electronic medical records and ...

AI Technical Summary

Problems solved by technology

Judging from the current research status: there is relatively little research work on the formal and specific quantitative description of knowledge reduction performance evaluation indicators and the construction of evaluation models, especially the research on the method of knowledge reduction performance evaluation in the cloud computing environment. There are still relatively few reports, which greatly restricts the application of knowledge reduction algorithms in the actual large-scale electronic medical records clinical intelligent diagnosis model, prescription behavior, and implementation of clinical pathways.

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