Latest AI and machine learning research in critical care for healthcare professionals.
Wrist-worn photoplethysmography (PPG) enables continuous monitoring of cardiopulmonary physiology, but reliable heart rate (HR) and respiratory rate (RR) estimation in free-living conditions remains challenging due to non-stationary motion artifacts that spectrally overlap with physiological dynamics. Existing signal-processing methods degrade under strong motion, while unconstrained deep learning...
Most published clinical-AI results are single models on a single dataset, difficult to reproduce, and rarely validated outside their training hospital. We built a broad, methodologically rigorous, reproducible clinical decision-support (CDS) suite spanning four families - intensive-care deterioration and outcomes, emergency- department triage, electrocardiographic interpretation, and clini- cal na...
Despite contributing substantially to clinician burnout, nursing documentation lacks empirical evidence distinguishing clinically essential from admin...
Precise prognostication in acute brain injury is limited by a lack of reliable biomarkers of consciousness available to clinicians at the bedside. The...
Intracranial aneurysms are often asymptomatic until rupture, which carries high mortality. Rupture risk assessment and treatment planning depend on bo...
BackgroundVentilator-associated pneumonia (VAP) is the most frequent nosocomial infection in critical care, affecting 20-36% of mechanically ventilate...
BackgroundInitiation of emergency dialysis, often requiring temporary catheter owing to unprepared definitive vascular access, is associated with infe...
Recent breakthroughs in 3D generation have advanced notably with the development of text-to-image diffusion model. However, existing methods remain tw...
Background: Motor neuron disease (MND) is a fatal neurodegenerative condition with significant clinical heterogeneity that is incompletely captured by...
Rapid and accurate pathogen identification is crucial for the clinical management of infectious diseases, particularly sepsis and severe respiratory i...
Can one graph represent every kind of LLM agent's run? A trace records what each step did, never what it relied on, the state it read, and the results...
Apnoea of prematurity is characterised by recurrent episodes of cessation of breathing and remains difficult to detect reliably using routinely monito...
Modern Referring Image Segmentation (RIS) systems generate multiple candidate masks per expression but rely on a simple heuristic--typically the argma...
Purpose: To develop and evaluate a deep learning model for automated quantification of breast arterial calcification (BAC) on screening mammography an...
Burst suppression (BS) is a clinically relevant electroencephalographic (EEG) pattern used to monitor sedation depth and brain activity in critically ...
Real-world clinical decision support requires reasoning over heterogeneous and longitudinal patient information rather than answering isolated medical...
Accurately estimating treatment effects in time series is essential for evaluating interventions in real-world applications, especially when treatment...
Delirium is a common and serious complication in the Intensive Care Unit (ICU), associated with increased morbidity, prolonged hospital stays, and hig...
Objective sleep assessment relies on polysomnography (PSG), yet clinical impact is often better reflected in patient-reported outcomes (PROs) such as ...
Involving end-users in the development of an AI tool is an important facilitator to its implementation. Usability testing was therefore conducted with...