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 ...

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 ...

Impax International Sustainable Economy Fund portfolio marginally underperformed MSCI EAFE benchmark, driven primarily by stock-specific effects and style tilts. Read more here.

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

Marketing professionals question whether "Generative Engine Optimization" accurately describes work focused on shaping ...

Purpose-built PIM combines supplier data intake, evergreen part intelligence, and data syndication to power scale, ...

Dung Thuy Nguyen (Vanderbilt University), Ngoc N. Tran (Vanderbilt University), Taylor T. Johnson (Vanderbilt University), Kevin Leach (Vanderbilt University) PAPER PBP: Post-Training Backdoor ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

Sophelio Introduces the Data Fusion Labeler (dFL) for Multimodal Time-Series Data - The only labeling and harmonization studio built for multimodal time-series with full provenance you can replay “dFL ...

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

New techniques are giving researchers a glimpse at the inner workings of AI models. Hundreds of millions of people now use chatbots every day. And yet the large language models that drive them are so ...