Human body health data automatic analysis system based on depth learning

Abstract

The invention discloses a human body health data automatic analysis system based on depth learning; the system comprises the following parts: a health data acquisition module used for gathering correlation health data of a to-be-analyzed human body, wherein said data includes inspection type data and description type data; a feature extraction module used for respectively extracting features of the obtained inspection type data and description type data via a depth convolution model; a data fusion module used for fusing features extracted by the feature extraction module via an adaptation fusion algorithm, and solving the user final evaluation value; an automatic analysis module used for inputting the final evaluation value into an intelligent diagnosis model so as to output an analysis result. In addition, the system uses the inspection type data and the description type data to build the intelligent analysis model, thus improving the diagnosis result accuracy.

Description

technical field [0001] The invention relates to the field of medical data analysis, in particular to a system for automatically analyzing human health data based on deep learning. Background technique [0002] At present, most of the diagnostic results of patients can only be obtained after comprehensive analysis by doctors based on the test results of patients. On the one hand, the workload of doctors is relatively large, and on the other hand, the requirements for doctors' work experience are high, otherwise misdiagnosis is easy to occur. [0003] In view of this, how to provide an automatic health data analysis system to assist manual disease diagnosis has become an urgent technical problem to be solved. Contents of the invention [0004] In order to solve the above problems, the present invention provides a system for automatically analyzing human health data based on deep learning. [0005] In order to achieve the above object, the technical scheme that the present i...

AI Technical Summary

Problems solved by technology

[0002] At present, most of the diagnosis results of patients can only be obtained after comprehensive analysis by doctors based on the test results of patients. On the one hand, the workload of doctors is relatively large, and on the other hand, the requirements for doctors' work experience are high, otherwise it is easy to misdiagnose.

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