The invention belongs to the technical field of
diabetes risk prediction, and provides a method and
system for predicting the
diabetes risk of children prediabetic
population, and the method comprises the following steps: S1, multi-
modal data fusion collection: collecting children clinical data, biochemical indexes, dynamic
blood glucose monitoring data and type 1 diabetes specific data; s2,
feature engineering and model construction: carrying out
feature engineering processing on the collected data, and extracting key indexes; s3, model training: performing risk prediction by using a
machine learning model, and outputting a
risk level and a confidence coefficient; s4, generating a personalized intervention scheme according to the
risk level; according to the method, the accuracy and reliability of prediction are remarkably improved by combining comprehensive analysis of multi-
modal data, key indexes can be accurately extracted through
feature engineering and model training, risk prediction can be carried out by utilizing a
machine learning model, and the development of child prediabetic people into diabetic patients is effectively delayed or prevented.