Machine learning reveals two main Parkinson's types and five subgroups

A new study led by researchers from VIB and KU Leuven shows that Parkinson's disease can be divided into distinct subtypes, ...
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 ...
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 ...
Scientific Research Publishing

A Wind Speed Prediction Model Based on Machine Learning in Guyuan Area ()

1 School of Atmospheric Sciences, Chengdu University of Information and Technology, Chengdu, China. 2 Guyuan Meteorological Bureau, Guyuan, China. 3 Jilin Provincial Institute of Meteorological ...
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 ...