Thyroid cancer risk prediction method based on heterogeneous medical data mining

Abstract

Thyroid cancer risk prediction method based on heterogeneous medical data mining, involving the field of thyroid cancer risk prediction, solves the existing problems of insufficient medical data model, poor ability of learning model to discover unknown categories, which affects the prediction ability of disease risk prediction model, etc. , collect medical data, and construct a heterogeneous medical record information network model; establish a learning model based on the discovery of unknown categories; realize the learning of unlabeled medical data; a medical reasoning model based on qualitative Bayesian; build an interval qualitative network as a medical reasoning model, verify Prediction conclusion; the invention accurately describes all kinds of semantic information and multiple relationships contained in the data records of patients in different time dimensions; combined with a semi-supervised prediction model that can discover "unknown categories", it realizes the learning of a large number of unlabeled medical data , to solve the problem of disease risk factor prediction; finally, bidirectional reasoning is carried out, and the inferred results have positive and negative polarity, and interval values ​​can be used to express the causal strength.

Description

technical field [0001] The invention relates to a thyroid cancer risk prediction method based on heterogeneous medical data mining. Background technique [0002] With the digital accumulation of electronic medical records and electronic health records, medical big data research has been highly valued by researchers in the medical and computer fields. Medical data itself integrates a large number, diversity, and rapidity to generate value. The four basic characteristics of big data also have the characteristics of variability, accuracy, complexity, and heterogeneity. Medical big data contains a wealth of medical knowledge, some of which have not yet been recognized by the medical community. Using this knowledge can not only assist medical treatment and improve medical quality, but also predict medical phenomena and effectively prevent and control diseases. Traditional medicine is the judgment and decision-making of small data, which completely depends on the experience and a...

AI Technical Summary

Problems solved by technology

[0017] The present invention provides a thyroid cancer risk prediction method based on heterogeneous medical data mining to solve the problems in the prior art that the medical data model is insufficient, the learning model has poor ability to discover unknown categories, and affects the prediction ability of the disease risk prediction model.

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