Machine Learning to Identify Predictors of Glycemic Control in Type 2 Diabetes: An Analysis of Target HbA1c Reduction Using Empagliflozin/Linagliptin Data

ConclusionsUsing both traditional and novel data analysis methodologies, this study identified baseline glycemic status as the strongest predictor of target glycemic control attainment. Machine learning algorithms provide an hypothesis-free, unbiased methodology, which can greatly enhance the search for predictors of therapeutic success in T2DM. The approach used in the present analysis provides an example of how a machine learning algorithm can be applied to a clinical dataset and used to develop predictions that can facilitate clinical decision making.
Source: Pharmaceutical Medicine - Category: Drugs & Pharmacology Source Type: research