First Experiences with the Identification of People at Risk for Diabetes in Argentina using Machine Learning Techniques

arXiv:2403.18631v1 Announce Type: new
Abstract: Detecting Type 2 Diabetes (T2D) and Prediabetes (PD) is a real challenge for medicine due to the absence of pathogenic symptoms and the lack of known associated risk factors. Even though some proposals for machine learning models enable the identification of people at risk, the nature of the condition makes it so that a model suitable for one population may not necessarily be suitable for another. In this article, the development and assessment of predictive …

abstract argentina arxiv challenge cs.lg diabetes identification machine machine learning machine learning models machine learning techniques medicine people proposals risk type