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

What’s the first thing you think of when you hear about ai security threats and vulnerabilities? If you’re like most people, your mind probably jumps to Large Language Model (LLM) ...

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 ...

More than half of transplant recipients in a large analysis developed chronic graft-versus-host disease, and 15% died from causes other than cancer relapse. Those numbers capture the uneasy truth of ...

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...

However, in indoor environments, non-line-of-sight (NLOS) signals significantly degrade the ranging performance of UWB ...

Facing strict privacy laws, telcos use AI-generated synthetic data as a compliant workaround to train ML models without exposing sensitive customer information.

Intramolecular charge transfer (ICT) is one of the most important photophysical mechanisms in organic fluorophores. Among ICT processes, TICT ...

Discover the impact of digital pathology on drug discovery and biomarker research this International Women’s Day with Dr ...

A machine learning-driven eNose detects ovarian cancer in blood plasma with 97 % sensitivity and specificity, offering a promising biomarker-agnostic approach.

Researchers at Academia Sinica and National Taiwan University Hospital have developed an AI-powered blood test that detects early-stage pancreatic cancer with near-perfect accuracy in validation ...