Diabetes Prediction Models Based on Machine Learning
Liu Bobo,
Kang Xiaofei,
Zhang Zongyue
et al.
Abstract:Objective to compare the predictive efficacy of random forest, BP neural network, gradient boosting tree and plain Bayesian models for the prevalence of diabetes. Practical application: by measuring the basic indicators such as individual height, weight, triglyceride, etc., the model can be used to predict the probability of individual disease, and then targeted to improve some indicators of the body, to achieve the effect of diabetes prevention intervention, and to provide new ideas for diabetes prevention re… Show more
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