Latest AI and machine learning research in critical care for healthcare professionals.
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...
Background: Osteoporosis and osteopenia are often undiagnosed until fragility fractures occur. Dual-...
Reinforcement Fine-Tuning (RFT) has established itself as a critical paradigm for the alignment of M...
Evaluating medical AI systems using expert clinician panels is costly and slow, motivating the use o...
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...
Evaluating medical AI systems using expert clinician panels is costly and slow, motivating the use o...
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...
Text-to-image (T2I) generative models achieve impressive visual fidelity but inherit and amplify dem...
Accurate estimation of cancer risk from longitudinal electronic health records (EHRs) could support ...
Multi-task visual anomaly detection is critical for car-related manufacturing quality assessment. Ho...
Current video benchmarks for multimodal large language models (MLLMs) focus on event recognition, te...
Although recent advances have improved the quality of 3D texture generation, existing methods still ...
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...
RL training of multi-turn LLM agents is inherently unstable, and reasoning quality directly determin...
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...