Latest AI and machine learning research in risk management for healthcare professionals.
Objective. EEG foundation models (FMs) report strong accuracy on clinical resting-state EEG. However, high accuracy under subject-disjoint cross-validation remains ambiguous: it can reflect a genuine clinical biomarker, or subject-identity features that correlate with the label. We name this the Identity Trap and ask whether it can be diagnosed at the representation level before fine-tuning. App...
Background: We previously examined the burden and predictors of sustained mental health care engagement in Ugandan first episode psychosis patients by retrospective chart review methods. However, the extensive requirements of chart reviews meant that we could only extract data from a random 10% sample of 1677 newly enrolled Ugandan first-episode psychosis patients at Butabika National Referral Men...
Our study evaluated whether a deep learning auto segmentation model combined with machine learning triage can streamline radiotherapy clinical trial q...
Introduction Obstructive lung diseases (OLDs) are responsible for high rates of illness and death worldwide. Inflammation, chronic airflow limitation,...
Andes orthohantavirus (ANDV), the primary etiological agent of hantavirus pulmonary syndrome (HPS) in South America, is uniquely capable of limited hu...
Background & Aims: Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD) is the leading cause of chronic liver disease in children. However...
In an era dominated by big data and machine learning, establishing valuable data collaboration has never been more critical. However, such collaborati...
Background: Accurate extraction of Human Phenotype Ontology (HPO) terms from clinical notes is essential for variant prioritization and genetic diagno...
Posttraumatic stress disorder (PTSD) is a prevalent and debilitating mental health condition with significant personal and societal impacts. Current c...
Automated pavement distress assessment requires more than image-level classification or coarse bounding box detection, demanding precise localization ...
Pressure injuries represent a significant healthcare challenge requiring early detection to prevent severe complications. While thermal imaging shows ...
Background: With growing impetus to integrate artificial intelligence (AI) tools into radiology, clinical practices must navigate workflow redesign. T...
Background Community-wide active case-finding (ACF) is being increasingly implemented as a tuberculosis (TB) elimination intervention. However, conven...
Long-horizon clinical simulation -- predicting how a patient's physiology evolves over years under specified interventions -- is central to chronic-di...
CLIP-style contrastive pretraining typically curates web-scale image-text pairs using sample-level filtering signals, often based on pair-level alignm...
Feed-forward 3D reconstruction has recently demonstrated strong generalization across diverse scenes, yet its performance in UAV imagery remains under...
Test-time adaptation (TTA) has recently emerged as a promising approach for improving time series forecasting (TSF) under distribution shift. Existing...
Querying the RDF Portal knowledge graph maintained by DBCLS, which aggregates approximately 60 life-science databases, requires proficiency in both SP...
Glioblastoma multiforme (GBM) is characterised by profound genomic heterogeneity and heavy-tailed gene-expression distributions that challenge convent...
Industrial visual inspection systems increasingly rely on deep classifiers whose heatmap explanations may appear visually plausible while failing to i...