The objective of this study is to evaluate the importance and impact of risk factors related to the incidence of hypoglycemia through an explainable machine learning method. This prospective study ...

This project implements a machine learning model to predict diabetes based on various health parameters. The aim is to assist healthcare professionals and patients in early diagnosis and intervention, ...

Objective: To characterize, via a predictive model using real-world data, patients with diabetes with a heightened probability of hospitalization. Methods: At the Endocrinology Unit of a tertiary ...

Significant predictors were selected on the training set using recursive feature elimination methods, followed by prediction model development using 7 machine learning algorithms (logistic regression, ...

Prediction model for type 2 diabetes mellitus and its association with mortality using machine learning in three independent cohorts from South Korea, Japan, and the UK: a model development and ...

Building a machine learning model that uses a dataset containing medical data of patients to predict if a person has diabetes or not.

STRENGTHS AND LIMITATIONS OF THIS STUDY Six models for predicting type 2 diabetes risk were constructed and compared based on machine learning methods. This study contributes to a better understanding ...

Background: The possible association between diabetes mellitus and dementia has raised concerns, given the observed coincidental occurrences. Objective: This study aimed to develop a personalized ...