Emergency Medicine

ICP-WAVES: Intracranial Pressure Waveform Analysis and Visualization for Enhanced Signal Processing.

OBJECTIVE: Intracranial pressure (ICP) waveform morphology reflects brain compliance and cerebrospinal fluid dynamics. Existing monitoring methods fail to fully capture complex temporal patterns nor enable real-time interactive analysis to improve clinical decision-making. METHODS: We trained a transformer-based foundation model to capture temporal dynamics and generate embeddings from physiologic...

AI-Powered Ambient Scribe Technology Experiences Among Emergency Physicians: Cross-Sectional, Mixed Methods Pilot Survey Study.

BACKGROUND: Health care organizations have started to implement artificial intelligence-powered ambient scribe technology in clinical documentation workflows. Early outpatient studies have shown mixed results. Few studies have evaluated ambient scribes in the emergency department (ED). Due to differences in setting and patient acuity between the ED and ambulatory clinics, there remains a pressing ...

Deep language model-based early recognition of out-of-hospital cardiac arrest from real-time emergency calls.

We developed a dynamic deep learning model (DyLM-OHCA) for early out-of-hospital cardiac arrest (OHCA) detection. Using 158,973 emergency call transcr...

Bayesian machine learning enables discovery of risk factors for hepatosplenic multimorbidity related to schistosomiasis.

One in 25 deaths worldwide is related to liver disease, and often with multiple hepatosplenic conditions. Yet, little is understood of the risk factor...

Predicting fracture risk in Y-TZP zirconia implants using radiomics-based artificial intelligence.

Attention-enhanced deep learning model for automated classification of hemorrhagic and ischemic stroke on CT imaging.

BACKGROUND: Stroke is a disease with extremely high mortality and disability rates worldwide. Hemorrhagic stroke and ischemic stroke require completel...

Prediction of high-flow nasal cannula failure in critically ill patients: a narrative review.

High-flow nasal cannula (HFNC) therapy is widely used for respiratory support in critically ill patients, offering benefits such as improved oxygenati...

Correction: Integrated network toxicology, machine learning and molecular docking reveal the mechanism of benzopyrene-induced periodontitis.

Di-(2-ethylhexyl) terephthalate promotes breast cancer progression: Multi-omics integrated experimental validation.

Di-(2-ethylhexyl) terephthalate (DOTP), as an alternative to phthalate plasticizers, has been widely used in sensitive fields such as food packaging a...

Adolescents Experiencing Both Bullying and Childhood Trauma: Longitudinal Patterns, Psychosocial Networks, and Risk Prediction.

Adolescents who experience both bullying at school and maltreatment within families are at heightened risk for psychological harm, yet little is known...

Rapid Diagnosis of Bacteremia in Febrile Pediatric Oncology Patients via Host-Response Infrared Spectroscopy of Blood and Machine Learning.

Bacteremia is a life-threatening complication and a leading cause of sepsis and septic shock in patients. Conventional diagnostic methods, such as blo...

An integrated physics-guided machine learning approach for predicting asphalt concrete fracture parameters.

Fairness analysis of machine learning predictions of aggression in acute psychiatric care.

Machine learning (ML) is increasingly being developed to support individualized risk assessment and de-escalation in acute psychiatry. However, ML alg...

Advancing trauma scoring through large language models: automated estimation of injury severity.

Characterization of the Sequence of Cytopenia after Total-body Irradiation using Unsupervised Machine Learning.

Hematopoietic acute radiation syndrome (H-ARS) elicits multidimensional effects, as total-body irradiation (TBI) induced myelosuppression results in d...

Hydrocarbon subsidy-stress and divergent reduced iron-manganese thresholds shape microbial resilience in anoxic aquifers.

The co-occurrence of geogenic metal mobilization and anthropogenic hydrocarbon contamination represents a pervasive hydro-biogeochemical challenge, ye...

Integrating multimodal data and deep learning for functional assessment and rehabilitation prediction after cerebral hemorrhage.

BACKGROUND: Intracerebral hemorrhage (ICH) is a leading cause of long-term disability, particularly in China. Post-stroke motor recovery exhibits cons...

Explainable machine learning prediction of tracheostomy after craniotomy for supratentorial intracerebral hemorrhage.

Accurate prediction of tracheostomy after craniotomy for supratentorial intracerebral hemorrhage (sICH) remains challenging. This study aimed to devel...

Self-Supervised Text-Vision Alignment for Automated Brain MRI Abnormality Detection: A Multicenter Study (ALIGN Study).

Purpose To develop a self-supervised text-vision framework to detect abnormalities on brain MRI scans by leveraging free-text neuroradiology reports, ...

Updates in Central Retinal Artery Occlusion.

BACKGROUND: Central retinal artery occlusion (CRAO) is a vision-threatening neuro-ophthalmic emergency, analogous to acute ischemic stroke. Delayed pr...