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 ...
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 ...

Lasers and drones assess health of world forests and help track climate change

Highly detailed 3D scans of dense tropical rain forest plots are enabling precise estimates of tree structure, volume and ...
IEEE

Smart Hybrid Energy Management for Renewable Energy Optimization using Random Forest Algorithm

Abstract: The present hybrid energy management systems are static rule-based. They are not able to respond to unpredictable alterations of renewable energy sources and internal load dynamics which ...
IEEE

Comparison of Novel Random Forest Algorithm over Gaussian Naïve Bayes for Improving Accuracy in Software Bug Prediction System

Abstract: Aim: This research work focuses on analyzing the performance of a proposed random forest method with that of Gaussian Naive Bayes in predicting software problems. Materials and Methods: The ...
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 ...