Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
The American Journal of Managed Care

Machine Learning May Enable Earlier Detection of CKD Risk Factors

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
SciELO

Comparative machine learning models for hypertension prediction in a cohort of patients with diabetes using routine clinical variables

Objective: To evaluate and to compare machine learning models for predicting hypertension in patients with diabetes using routine clinical variables. Methods: Using Behavioral Risk Factor Surveillance ...
Frontiers

Early prediction of gestational diabetes mellitus using machine learning-integrated metabolomic and clinical features

Gestational diabetes mellitus (GDM), a prevalent metabolic disorder associated with pregnancy, which often postpones intervention until after metabolic complications have developed. This study seeks ...
Scientific Research Publishing

Kasahun, M. and Legesse, A. (2024) Machine Learning for Urban Land Use/Cover Mapping: Comparison of Artificial Neural Network, Random Forest and Support Vector Machine, a Case ...

ABSTRACT: This research aims to explore changes in Land Use and Land Cover (LULC) and how LULC have an influence on the Land Surface Temperature (LST) in Rupandehi district. Multiple Landsat imagery ...
IEEE

Performance Metrices Analysis for Diabetes Prediction Using Machine Learning Algorithm

Abstract: Diabetes is the among of the chronic diseases which is every year the number of deaths increases to the diabetes patients. Despite the different ages, diabetes can either be inherited ...
Frontiers

Advanced Supervised Machine Learning Techniques for Accurate Prediction of Diabetes Mellitus Using Feature Selection

The final, formatted version of the article will be published soon. Background): Diabetes Mellitus (DM) is a chronic metabolic disorder that poses a significant global health challenge, affecting ...