Donation after circulatory death (DCD) procurements provide an opportunity to alleviate the limited organ supply for solid ...

We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...

Researchers successfully developed a machine learning-based method for predicting symptom deterioration in patients with cancer.

A machine learning algorithm used gene expression profiles of patients with gout to predict flares.

Cellarity, a clinical-stage biotechnology company developing Cell State-Correcting therapies through integrated multi-omics and AI modeling, today announced the publication of a seminal manuscript in ...

Discover how a machine-learning drug toxicity prediction model enhances the predictive power of AI in drug trials, boosting ...

The CT-based whole-lung radiomic nomogram accurately identifies AECOPD and offers a robust tool for clinical diagnosis and treatment planning.

According to recent analysis by Markntel Advisors, the Global AI Model Risk Management (MRM) Market is experiencing accelerated growth, ...

Marine oil spills are among the most severe environmental hazards, threatening aquatic ecosystems, coastal economies, and biodiversity. Traditional detection methods, based on manual observation, ship ...

In the UK, there was a case where TGN1412, an immunotherapy under development, triggered a cytokine storm within hours of administration to humans, leading to multiple organ failure.

DILI is one of the most significant safety challenges in developing therapeutics today, as hepatic safety events undetected in preclinical testing can occur in patients leading to clinical trial ...

Ransomware monetizes downtime. Integrity attacks monetize trust. They threaten the reliability of the very intelligence layer ...