Machine learning based study for the classification of Type 2 diabetes mellitus subtypes

Jose Luis Gonzalez-Compean, Ivan Lopez-Arevalo, Edwyn Aldana-Bobadilla and Dr. Nelson Emmanuel Ordoñéz Guillén

Abstract

Data-driven diabetes research has increased its interest in exploring the heterogeneity of the disease, aiming to support in the development of more specific prognoses and treatments within the so-called precision medicine. Recently, one of these studies found five diabetes subgroups with varying risks of complications and treatment responses. Here, we tackle the development and assessment of different models for classifying Type 2 Diabetes (T2DM) subtypes through machine learning approaches, with the aim of providing a performance comparison and new insights on the matter.

https://doi.org/10.1186/s13040-023-00340-2