Provided is a disease risk analysis method, relating to data processing technology, comprising: obtaining a training data set and performing classification to obtain a classified data set (S1); using the classified data set to train a plurality of pre-built weak classifiers, and selecting a plurality of target weak classifiers from the plurality of trained weak classifiers and aggregating the target weak classifiers into a disease model (S2); obtaining a user data set to be determined, and pre-processing the user data set to be determined to obtain a target data set (S3); establishing an index relationship between the target data set and the classified data set (S4); matching the target data set with the classified data set according to the index relationship to obtain a matched data set (S5); using the disease model to analyze and calculate the matched data set to obtain a disease analysis result (S6). In addition, the invention also relates to blockchain technology; basic data and/or feature data can be stored in a blockchain node. The invention can solve the problems of low analysis efficiency and low accuracy of disease risk analysis.
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