Minnesota passes ban on fake AI nudes; app makers risk $500K fines

This week, Minnesota became the first state to pass a law banning nudification apps that make it easy to “undress” or ...
The LancetOpinion

Who's really in the loop? Rethinking oversight in AI-assisted health care

Human-in-the-loop oversight is widely invoked as a safeguard against potential harm from artificial intelligence (AI) used in ...
Hospital Healthcare Europe

Closing the gender gap in acute coronary syndrome: GEDI-ACS registry insights

Prof Alaide Chieffo provides insight into how the GEDI-ACS study is redefining the understanding and management of ACS in ...
BMJ

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...
chromatographyonline

Optimizing HSSE-GC-MS and Machine Learning for Forensic Gender Classification from Human Scent

Researchers have optimized a headspace sorptive extraction (HSSE) method coupled with gas chromatography-mass spectrometry (GC-MS) to analyze human scent traces left on clothing. By extracting ...
Scientific Research Publishing

Buolamwini, J., & Gebru, T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings of Machine Learning Research, 81, 77-91.

ABSTRACT: The ubiquitous use of biometric technology in contemporary society, from unlocking smartphones to enforcing border control and law, has raised concerns regarding its impact on minority ...
The Lancet

When to and when not to use machine learning in risk prediction models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
The New York Times

48 Hours Without A.I.

It’s everywhere, as the author learned the hard way while making as little contact as possible with machine learning and generative artificial intelligence. It’s everywhere, as the author learned the ...
Frontiers

Explainable machine learning model for predicting the outcome of acute ischemic stroke after intravenous thrombolysis

Acute ischemic stroke (AIS) patients often experience poor functional outcomes post-intravenous thrombolysis (IVT). Novel computational methods leveraging machine learning (ML) architectures ...
BMJ

Predicting cardiovascular events from routine mammograms using machine learning

10 The George Institute for Global Health, School of Public Health, Imperial College London, London, UK Background Cardiovascular risk is underassessed in women. Many women undergo screening ...