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 ...

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% ...

Introduction Frailty is a common condition in older adults with diabetes, which significantly increases the risk of adverse health outcomes. Early identification of frailty in this population is ...

Diabetes mellitus is a metabolic disorder categorized using hyperglycemia that results from the body’s inability to adequately secrete and respond to insulin. Disease prediction using various machine ...

ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...

Deep learning-based prediction models outperformed traditional machine learning models, namely logistic regression, decision tree, naive Bayes, random forest, and support vector machine, on all the ...