The March 2026 issue of NEJM Catalyst Innovations in Care Delivery is a special theme issue on the hard work of implementing artificial intelligence in real-world ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

A team of UCSF researchers successfully tested several mainstream AI agents for the ability to analyze big data on women's ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

AI optimists envision a future where artificial general intelligence (AGI) surpasses human intelligence, but the path remains riddled with scientific and logistical hurdles.

To his credit, Kasy is a realist here. He doesn’t presume that any of these proposals will be easy to implement. Or that it will happen overnight, or even in the near future. The troubling question at ...

One example involved a system built by a summer intern for his own project work. The tool geolocates devices within a drawing set and links them to a digital twin of the facility. Instead of searching ...

Historian Philip Decker, mathematician Victor Geadah, computer scientist Sayash Kapoor, and literary scholar Eliana Rozinov are this year’s Porter Ogden Jacobus Fellows.

In an early test of how AI can be used to decipher large amounts of health data, researchers at UC San Francisco and Wayne State University found that generative AI tools could perform orders of ...