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

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 ...

"Medical Genomics" research group at ISTA "Data Science, Machine Learning, and Information Theory" research group at ISTA Al Depope, Jakub Bajzik, Marco Mondelli, and Matthew R. Robinson. 2026. Joint ...

Global climate models capture many of the processes that shape Earth's weather and climate. Based on physics, chemistry, ...

Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the visual system. Through accurate eye center annotation, physicians can observe ...

Field-level analysis examines how ranking algorithms shape consumer trust, visibility, and competition in local service ...

Winning in AI-driven search requires redesigning the enterprise operating model around eligibility, governance, and ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Estimating the number of triangles in a graph is a fundamental problem and has found applications in many fields. This ...

Smart Bidding and Meta’s delivery systems have leveled the field. To scale PPC, fix creative fatigue, increase asset volume, and test faster.

To prevent algorithmic bias, the authors call for multivariable modeling frameworks that jointly incorporate biological sex, genetic ancestry, and gender-related life-course exposures.

Tempus HRD-RNA is an AI-driven, 1,660-gene logistic regression model designed to identify patients likely to respond to ...