A new study led by researchers from VIB and KU Leuven shows that Parkinson's disease can be divided into distinct subtypes, ...
Researchers use machine learning and genetic analysis to uncover type 1 diabetes risk factors, improving prediction accuracy ...
Prof Alaide Chieffo provides insight into how the GEDI-ACS study is redefining the understanding and management of ACS in ...
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 ...
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 ...
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 ...
Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
Sarcopenia has a high incidence among patients undergoing maintenance hemodialysis (MHD), significantly increasing the risk of falls, fractures, and mortality. Traditional diagnostic methods, however, ...
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 ...
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