MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...

AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...

Structural economic models, while parsimonious and interpretable, often exhibit poor data fit and limited forecasting performance. Machine learning models, by contrast, offer substantial flexibility ...

Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, methicillin-resistant Staphylococcus aureus (MRSA) accounted for more than 100,000 global ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

See how machine learning is spotting Alzheimer’s years before symptoms begin—using brain scans to help guide earlier, more ...