Disease analysis method and device, electronic equipment and storage medium

Abstract

The invention relates to an artificial intelligence technology, and discloses a disease analysis method, which comprises the steps: extracting feature data from case information of a preset type of disease, and performing vectorization processing to obtain a feature vector; training a to-be-trained disease analysis model according to the feature vector and an initial model gradient obtained from aserver to obtain an updated model gradient, and sending the updated model gradient to a server through encryption processing; when the model gradient in the convergence state transmitted by the server is received, updating the model gradient of the disease analysis model to be trained by using the model gradient in the convergence state to obtain a standard disease analysis model; and analyzing the case information of the target user by using the standard disease analysis model to obtain an analysis result of the preset type of disease. The invention further provides a disease analysis device, electronic equipment and a storage medium. The invention also relates to a blockchain technology, and the analysis result can be stored in a blockchain node. The accuracy of disease analysis can beimproved.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a disease analysis method, device, electronic equipment and computer-readable storage medium. Background technique [0002] Analyzing diseases and early detection and treatment are important means to reduce patient mortality. Taking thyroid disease as an example, thyroid nodules are a chronic disease, and the pathological features of thyroid nodules are not obvious at the initial stage, but once they develop, they deteriorate rapidly and even endanger human life. [0003] The current analysis of thyroid nodule disease requires the analysis of various data such as clinical data, blood test data, ultrasound data, fine needle aspiration test data, etc. A single hospital conducts a unified analysis of the cases to obtain the thyroid nodule risk detection standard, but a single hospital After all, the number of cases is limited, and accurate analysis and detec...

AI Technical Summary

Problems solved by technology

[0003] The current analysis of thyroid nodule disease requires the analysis of various data such as clinical data, blood test data, ultrasound data, fine needle aspiration test data, etc. A single hospital conducts a unified analysis of the cases to obtain the thyroid nodule risk detection standard, but a single hospital After all, the number of cases is limited, and accurate analysis and detection standards cannot be obtained

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