Abstract:Background
Given tongue features and basic features, this study aimed to develop and assess a non-invasive machine learning model to perform regression prediction on fasting plasma glucose and glycated haemoglobin which will help optimize diabetes risk warning.
Methods
We collected the basic features, tongue features and blood features of the subjects. Using machine learning algorithms to analyze these data, we built models to predict fasting plasma glucose and glycated haemoglobin. Then the performance of t… Show more
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