Multivariable prediction model of complications derived from diabetes mellitus using machine learning on scarce highly unbalanced data

ConclusionsThis ML model can be applied to predict CHD, CKD, and MOR. The success of ML predictions lies in the clinical definition of initial variables and their simplification for obtaining variables based on which the algorithms can identify patients that are likely to develop a complication. For clinical application of this system, it is necessary to assess the cross performance of metrics, as found here (accuracy higher 95% and F1-Score higher than 80%).
Source: International Journal of Diabetes in Developing Countries - Category: Endocrinology Source Type: research