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 ...

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 ...

"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 ...

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

Learn how AI-driven personalization transforms customer loyalty. Explore predictive modeling and data strategies for ...

A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...

Steffen Schmitz-Valckenberg, MD, discusses how optical coherence tomography-based models may enable rapid, noninvasive assessment of functional loss in GA at Angiogenesis 2026.

A particle collision reconstructed using the new CMS machine-learning-based particle-flow (MLPF) algorithm. The HFEM and HFHAD signals come from the ...

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