Latest AI and machine learning research in critical care for healthcare professionals.
Kernel methods have been extensively utilized in machine learning for classification and prediction ...
Offline Reinforcement Learning (RL) promises the recovery of optimal policies from static datasets, ...
Generative models have achieved impressive fidelity in text-to-image synthesis, yet struggle with co...
Self-supervised learning (SSL) methods based on Siamese networks learn visual representations by ali...
Accurate and timely seizure detection from Electroencephalography (EEG) is critical for clinical int...
Klebsiella pneumoniae is a major causative agent of hospital-acquired infections worldwide, contribu...
Medical audio classification remains challenging due to low signal-to-noise ratios, subtle discrimin...
Camera-based 3D semantic scene completion (SSC) offers a cost-effective solution for assessing the g...
Privacy preservation is a prerequisite for using video data in Operating Room (OR) research. Effecti...
Purpose: Ventilator-associated pneumonia (VAP) remains one of the most serious hospital-acquired inf...
Sleep is essential for physical and mental health, yet large-scale assessment of sleep stages and sl...
Background: Childhood T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic ma...
Pain management in intensive care usually involves complex trade-offs between therapeutic goals and ...
Respiratory syncytial virus (RSV) remains the leading cause of severe respiratory infections in infa...
Sepsis remains one of the most complex and heterogeneous syndromes in intensive care, characterized ...
BACKGROUND Medical large language models (LLMs) achieving high benchmark accuracy exhibit unexplaine...
Echocardiography is a cornerstone for managing heart failure (HF), with Left Ventricular Ejection Fr...
Background: Delayed or missed diagnosis of congenital heart disease (CHD) contributes to excess pedi...
Due to silence in early stages, lung cancer has been one of the most leading causes of mortality in ...
We investigate whether temporal embedding models trained on longitudinal electronic health records c...
Accurate clinical prognosis requires synthesizing structured Electronic Health Records (EHRs) with r...