Latest AI and machine learning research in critical care for healthcare professionals.
Objective: To test whether machine learning (ML) models trained on tidal breathing flow time series ...
Vision-language models (VLMs) are increasingly used as automated judges for multimodal systems, yet ...
We present a suite of foundational, outcome prediction models for critically ill patients, developed...
Background & Aims: Accurate assessment of clinical malnutrition using anthropometric and functional ...
Training reliable respiratory sound classification models remains challenging due to the limited siz...
Progression to dialysis or end-stage renal disease is a rare but clinically important outcome. Clini...
Background: Mechanical ventricular unloading and systemic circulatory support with left ventricular ...
Sepsis is a leading cause of in-hospital mortality, yet systematically evaluating temporal adherence...
Respiratory airflow signals provide critical insight into breathing mechanics, yet conventional anal...
Multimodal clinical records contain structured measurements and clinical notes recorded over time, o...
Timely and interpretable early warning of sepsis remains a major clinical challenge due to the compl...
Accurate prediction of future risk and disease progression in sepsis is clinically important for ear...
Objective: Post-traumatic epilepsy (PTE) is a debilitating neurological disorder that develops after...
Human-object interaction (HOI) detection aims to detect interactions between humans and objects in i...
Semiconductor failure analysis (FA) requires engineers to examine inspection images, correlate equip...
Recent advances in image editing have heightened the need for reliable Image Editing Quality Assessm...
Current video benchmarks for multimodal large language models (MLLMs) focus on event recognition, te...
Background: The Therapeutic Distance framework (Paper 1) achieved AUC 0.61 for orbit-based mortality...
Conventional multi-image super-resolution (MISR) methods, such as burst and video SR, rely on sequen...
Objective: To develop a workflow that transforms electronic health record data into machine learning...
Type 2 diabetes case reports describe complex clinical courses, but their timelines are often expres...