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 ...

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 ...

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

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

A red-hot Manchester City are making the trip south to the East Midlands on Saturday afternoon to take on Nottingham Forest in their final test of the calendar year. What began to look like a runaway ...

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

ABSTRACT: Despite its significant impacts on climate, environment, and public health, air pollution monitoring in Africa is still sparse. This study developed a machine learning framework of four ...

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...

XRP is back above the $3 mark after a shaky few weeks, regaining momentum and breathing new hope into the market. Hovering at around $3.04 at the time of writing, the cryptocurrency is up over 1.72% ...

Abstract: The amalgamation of IoT with machine learning techniques presents an innovation in the healthcare sector by offering novel approaches to disease prediction and management. The work describes ...