A study published in The Journal of Engineering Research at Sultan Qaboos University presents an advanced intrusion detection system (IDS) designed to improve the accuracy and efficiency of ...

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

Immunoprecipitation-enhanced blood-based biomarkers are improving early diagnosis of Alzheimer’s disease by enabling more sensitive detection.

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 ...

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

Introduction Cerebral palsy (CP) is a non-progressive condition involving movement and muscle tone difficulties due to injury to the developing brain. Most cases arise around birth, but a smaller ...

A study published in Gastroenterology reports that a blood test-based scoring tool can help identify previously undiagnosed ...

Objective Unplanned hospital readmissions within 30 days of discharge measure the quality of healthcare. This study aims to ...

Objectives To evaluate whether type 2 diabetes mellitus (T2DM) presence and severity are associated with differences in global and domain-specific cognitive function among US adults, using ...

Completion of Updated BFS Provides Robust Financials for Project Financing EcoGraf Limited is pleased to announce the completion of its updated Bankable Feasibility Study for its Epanko Graphite ...

A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.