Emergency Medicine

Automated estimation of drain output in postoperative patients using deep learning on clinical images.

Postoperative drains are essential components of care in general surgery and intensive care units, where accurate monitoring of drain output is critical for detecting complications such as hemorrhage, anastomotic leakage, or infection. Despite its importance, output measurement is still performed manually, which is time-consuming, exposes staff to biohazardous fluids, and is prone to documentation...

Graph theory reveals functional connectome disruptions in adolescent major depressive disorder with childhood trauma.

BACKGROUND: Childhood trauma (CT) is a major risk factor for adolescent major depressive disorder (MDD), yet its neurobiological underpinnings and longitudinal treatment effects remain poorly characterized. METHODS: Leveraging graph theory and resting-state fMRI, we analyzed in 343 adolescents with MDD aged 10 - 18 years, including 211 with a history of childhood trauma (MDD-CT) and 106 without ch...

Mechanism exploration of di(2-ethylhexyl) phthalate (DEHP)-induced hepatocellular carcinoma via network toxicology and molecular docking analysis.

Chemical contaminants and fish: implications for health and ecosystem sustainability.

Chemical pollutants in aquatic ecosystems pose a significant and growing threat to fish health and overall ecosystem sustainability. This review highl...

Comparative performance of manual triage systems and ML models in predicting clinical outcomes among patients transported to the emergency department by emergency medical services.

Reconstruction of Under-Sampled Images and Concurrent Optimization of Sampling Masks for 3D Carotid Simultaneous Non-Contrast Angiography and intraPlaque Hemorrhage MRI With Model Based Deep Learning Architecture (deepSNAP).

PURPOSE: To improve the imaging efficiency of 3D carotid simultaneous noncontrast angiography and intraplaque hemorrhage (SNAP) MRI by reconstruction ...

Context-Guided Mixture-of-Experts with Multimodal LLMs for Lesion Detection in Buccal Mucosa Images.

INTRODUCTION AND AIMS: Oral lesions are highly prevalent globally, and oral cancer ranks among the most common malignancies, underscoring the need for...

AI-driven navigated hematoma aspiration vs. conservative treatment for spontaneous intracerebral hemorrhage: study protocol for a randomized controlled trial.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) remains one of the most devastating types of stroke, with high mortality and long-term disabili...

Development and External Validation of a Deep Learning Model to Predict Mortality in Aneurysmal Subarachnoid Hemorrhage Using Admission Computed Tomography.

BACKGROUND AND OBJECTIVES: Traditional prognostication after aneurysmal subarachnoid hemorrhage depends on subjective clinical grading and radiologica...

Integration of AHRR methylation, heavy metals, and clinical characteristics for urothelial carcinoma risk stratification: An explainable artificial intelligence approach.

The short metabolic half-life of conventional tobacco biomarkers often limits their ability to reflect cumulative toxicological damage, which may comp...

Deep learning prediction of contrast extravasation versus intracranial hemorrhage after thrombectomy in patients with acute stroke.

AI Triage of Normal Chest Radiographs: A Silent Trial and Failure Analysis.

Chest radiography is the most frequently performed imaging examination worldwide, and increasing demand has contributed to reporting delays in many he...

Computational identification of diagnostic biomarkers linking Dibutyl phthalate exposure to ovarian cancer through network toxicology and machine learning.

Purchasing and Using an Artificial Intelligence Algorithm for Fracture Detection: Point-One of the Most Justifiable and Mature Applications in Radiology Today.

Purchasing and Using an Artificial Intelligence Algorithm for Fracture Detection: Counterpoint-Practical Barriers to Clinical Adoption.

Plaque-Level Machine Learning Prediction of Intraplaque Hemorrhage in Carotid Arteries Using Computed Tomography Angiography.

BACKGROUND: Carotid artery plaques, especially those with intraplaque hemorrhage (IPH), are significant contributors to ischemic stroke. Although high...

Machine Learning-Based Prediction of Critical Deterioration in the PICU.

BACKGROUND: Existing PICU early warning systems lack sufficient accuracy and timeliness for effective preparation. Machine learning approaches may imp...

FDA-authorized oncology artificial intelligence and machine learning devices and their clinical evidence: A cross-sectional analysis.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) tools are increasingly embedded in cancer care, yet the scope of U.S. Food and Drug...

Exploring the toxicological impact of perfluorooctanoic acid and perfluorooctane sulfonate on glioblastoma through network toxicology, machine learning, and multi-dimensional bioinformatics analysis.

Exposure to perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) has been associated with the development of various malignant tumors. H...

Development of Mind-Body Interventions for the Emergency Department.

Emergency department (ED) visits are a common experience that most individuals will have across their lifetime. ED-based evaluation for acute complain...