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 ...

A recent review concluded that artificial intelligence (AI) is rapidly transforming the diagnosis and treatment of haematological malignancies by enhancing diagnostic accuracy and ...

Diabetes affects over 537 million adults globally, with early detection critical for effective treatment and management. This project develops a machine learning classification model to predict ...

Background: Stress-induced hyperglycemia (SHG) represents a significant metabolic complication in non-diabetic cardiac surgery older adult patients, with substantial implications for postoperative ...

This project aims to build a machine learning model that accurately predicts whether a patient has diabetes based on medical measurements. The dataset is highly imbalanced (65% non-diabetic vs 35% ...

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, ...

The recent surge in demand for timely and accurate health information has highlighted the need for more advanced data analysis tools. To reduce the incidence of preventable medical errors, ...

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 ...

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 ...