Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

MIT researchers developed a method that generates more accurate uncertainty measures for certain types of estimation. This could help improve the reliability of data analyses in areas like economics, ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic ...

People have long turned to support groups to find assurance and connection from others with similar experiences in dealing ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Dario Amodei, the C.E.O. of the artificial-intelligence company Anthropic, has been predicting that an A.I. “smarter than a Nobel Prize winner” in such fields as biology, math, engineering, and ...

Introduction The provision of optimal care for older adults with complex chronic conditions (CCCs) poses significant challenges due to the interplay of multiple medical, pharmacological, functional ...

Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...

Robot-assisted surgery (RAS) enhances surgical precision and extends surgeons’ capabilities. However, its effects on the cognitive and physical states of surgeons remain poorly understood. It is ...