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 ...
Acute myocardial infarction (AMI) is significantly influenced by meteorological conditions; however, leveraging meteorological data to predict AMI incidence remains challenging. This study aimed to ...
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 ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
Acute ischemic stroke (AIS) patients often experience poor functional outcomes post-intravenous thrombolysis (IVT). Novel computational methods leveraging machine learning (ML) architectures ...
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 ...
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