A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...

One of the most immediate impacts of AI in medical genetics lies in diagnosis, particularly for rare and complex genetic ...

This article explores how single-cell multiomics and spatial transcriptomics are illuminating early pregnancy, uncovering ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

The progression of glaucoma was accurately predicted by machine learning models based on structural, functional and vascular biomarkers, including those from OCT angiography, according to data ...

A newly developed artificial intelligence (AI) model is highly accurate in predicting blood loss in patients undergoing high-volume liposuction, reports a study in the January issue of Plastic and ...

A newly developed artificial intelligence (AI) model is highly accurate in predicting blood loss in patients undergoing ...

How AI-driven admission and discharge prediction can help emergency departments improve throughput, reduce delays, and support clinicians without replacing clinical judgment.

A newly developed artificial intelligence (AI) model is highly accurate in predicting blood loss in patients undergoing high-volume liposuction, reports a study in the January issue of Plastic and ...

Objective Chronic kidney disease (CKD) arises due to uncontrolled hypertension (HTN). HTN significantly increases the risk of complications in vital organs, mainly the kidneys. If hypertensive ...

Introduction Atrial fibrillation (AF) is the leading cause of cardioembolic stroke and is associated with increased stroke severity and fatality. Early identification of AF is essential for adequate ...

Background Despite anticoagulation, patients with atrial fibrillation (AF) experience persistent elevated cardiovascular risk ...