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 Purdue University digital forestry team has created a computational tool to obtain and analyze urban tree inventories on ...

Researchers use mini plasma explosions to encode the equivalent of two million books into a coaster-sized device. The method ...

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 ...

Abstract: Inspired by soft-bodied animals, soft continuum robots provide inherently safe and adaptive solutions in robotics, especially suited for applications requiring gentle interactions. However, ...

There's been a seismic shift in science, with scientists developing new AI tools and applying AI to just about any question that can be asked. Researchers are now putting actual seismic waves to work, ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

If the FDA follows through with the proposed guidelines, and they are not fatally twisted by pressure from the medical ...

The National Institutes of Health failed to protect brain scans that an international group of fringe researchers used to argue for the intellectual superiority of white people. Credit...Ben Denzer ...

As a qualitative researcher, Ruth Abrams, a senior lecturer at the University of Surrey, doesn’t usually share her data. “It feels like a private moment between the researcher and the participant,” ...

The 2026 Statistics Update uses language that conveys respect and specificity when referencing race and ethnicity. Instead of referring to groups very broadly with collective nouns (eg, Blacks, Whites ...