Latest AI and machine learning research in critical care for healthcare professionals.
Congenital anomalies of the kidney and urinary tract (CAKUT) are the leading cause of pediatric kidney failure, but predicting individual progression remains challenging. This multicenter study developed and validated POCC, a machine learning model for predicting kidney failure risk at 1, 3, and 5 years post-diagnosis in CAKUT patients. Two versions were created using data from 2,249 children. The...
Large language models (LLMs) continue to struggle with knowledge-intensive questions that require up-to-date information and multi-hop reasoning. Augmenting LLMs with hybrid external knowledge, such as unstructured text and structured knowledge graphs, offers a promising alternative to costly continual pretraining. As such, reliable evaluation of their retrieval and reasoning capabilities becomes ...
Kernel methods have been extensively utilized in machine learning for classification and prediction tasks due to their ability to capture complex non-...
Existing multimodal retrieval benchmarks largely emphasize semantic matching on daily-life images and offer limited diagnostics of professional knowle...
Offline Reinforcement Learning (RL) promises the recovery of optimal policies from static datasets, yet it remains susceptible to the overestimation o...
Generative models have achieved impressive fidelity in text-to-image synthesis, yet struggle with complex compositional prompts involving multiple con...
Self-supervised learning (SSL) methods based on Siamese networks learn visual representations by aligning different views of the same image. The multi...
Accurate and timely seizure detection from Electroencephalography (EEG) is critical for clinical intervention, yet manual review of long-term recordin...
Klebsiella pneumoniae is a major causative agent of hospital-acquired infections worldwide, contributing substantially to morbidity, mortality, and he...
Medical audio classification remains challenging due to low signal-to-noise ratios, subtle discriminative features, and substantial intra-class variab...
Camera-based 3D semantic scene completion (SSC) offers a cost-effective solution for assessing the geometric occupancy and semantic labels of each vox...
Multimodal Large Language Models (MLLMs) have significantly advanced vision-language understanding. However, even state-of-the-art models struggle wit...
Generative models trained using self-supervision of tokenized electronic health record (EHR) timelines show promise for clinical outcome prediction. T...
Privacy preservation is a prerequisite for using video data in Operating Room (OR) research. Effective anonymization relies on the exhaustive localiza...
Purpose: Ventilator-associated pneumonia (VAP) remains one of the most serious hospital-acquired infections in the intensive care unit (ICU), with hig...
Sleep is essential for physical and mental health, yet large-scale assessment of sleep stages and sleep apnea is limited by the cost and burden of cli...
Background: Childhood T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy with poor prognosis. Differently from B-c...
Trajectory planning is a core task in autonomous driving, requiring the prediction of safe and comfortable paths across diverse scenarios. Integrating...
Pain management in intensive care usually involves complex trade-offs between therapeutic goals and patient safety, since both inadequate and excessiv...
Respiratory syncytial virus (RSV) remains the leading cause of severe respiratory infections in infants, the elderly, and the immunocompromised. Altho...