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 ...

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

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

Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...

From PageRank to AI Overviews, Google’s understanding of authority evolved. Here's why brand legitimacy now drives sustainable visibility.

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

In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...

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

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...