Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

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

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

Read more about AI-driven air quality system promises faster, more reliable urban health warnings on Devdiscourse ...

Unomedical, which supplies diabetes tech firms including Medtronic, Tandem Diabetes Care and Beta Bionics, received more than 5,000 complaints about leaking infusion sets between 2023 and 2025.

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 ...

Artificial intelligence has moved from pilot projects to a central role in many life sciences strategies. What began as a set ...

A machine learning model predicted cardiac tamponade during AF ablation with high accuracy. Learn how XGBoost may improve risk stratification.

Medical physicist Todd McNutt explains how Plan AI, an artificial intelligence-powered plan quality software solution, uses data mining to streamline and improve radiotherapy planning for cancer treat ...

AI systems are beginning to build and improve themselves. But without a verification layer, trust, safety and accountability ...

The use of AI in attacks is also creating future issues for cybersecurity, with agentic AI being used to undertake harvest now, decrypt later strategies to collect data and store it for when quantum ...