Emergency Medicine

Evaluation of deep learning architectures for predicting ligand interactions with neurologically relevant GPCRs.

G protein-coupled receptors (GPCRs) are therapeutic targets for over 30% of approved drugs, yet specific GPCR subtypes act as molecular initiating events in several neurotoxic adverse outcome pathways. Therefore, knowledge of GPCR-ligand interactions is critical for drug discovery and computational toxicology. However, accurate predictions of GPCR-ligand binding can be challenging due to receptor ...

Chest Radiograph-based Artificial Intelligence for Osteoporosis: Accuracy and Associations With Fracture and Mortality.

OBJECTIVES: To evaluate an AI tool for opportunistic osteoporosis screening using chest radiographs (CXRs), focusing on its diagnostic accuracy against dual-energy x-ray absorptiometry (DXA) and associations with long-term risks of fracture and mortality. MATERIALS AND METHODS: This retrospective, external validation study included a health checkup cohort with same-day CXR-DXA pairs and a chronic ...

Clinician-supervised large language AI model after-discharge instruction generation for common emergency department presentations.

OBJECTIVES: After-discharge instructions often fail due to poor usability and language misalignment. We evaluated a clinician-supervised method for ge...

Fast MRI of bones in the knee - An AI-driven reconstruction approach for adiabatic inversion recovery prepared ultra-short echo time sequences.

PURPOSE: Inversion recovery prepared ultra-short echo time (IR-UTE)-based MRI enables radiation-free visualization of osseous tissue. However, achievi...

Machine Learning Prediction of Postoperative Mortality in Older Emergency Surgery Patients.

INTRODUCTION: The older adult population account for 35% of emergency general surgery (EGS) admissions and have an increased risk-adjusted odds of mor...

Artificial Intelligence (AI): Some fundamentals to know its place and potential in forensic toxicology.

Bouncing back from stress: objective markers of expressive flexibility and resilience in emergency healthcare workers using computer vision.

Healthcare workers (HCWs) in emergency departments face significant mental health risk due to chronic stressors and repeated trauma, yet symptom under...

From Symptom Control to Precision Supportive Oncology: Integrating Artificial Intelligence in Supportive Oncology for Gastrointestinal Cancers.

PURPOSE OF REVIEW: Gastrointestinal (GI) cancers are among the most common malignancies worldwide and impose a substantial symptom burden from diagnos...

An explainable artificial intelligence framework for clinical decision support in stroke discharge planning.

BACKGROUND: Stroke, a leading cause of global mortality and disability, requires accurate prediction of discharge outcomes to support early care plann...

Diagnostic capability of large language models in critically ill patients: a prospective single-centre study comparing ChatGPT, Claude, and Gemini with emergency physicians.

BACKGROUND: Clinical decision-making requires integrating history, physical examination, laboratory, and imaging data. In the emergency department (ED...

A pH-Calibrated Multi-Analyte MXene Aerogel Electrochemical Platform Assisted by Interpretable Machine Learning for CSF-Based Prescreening of Postoperative Bacterial Meningitis.

Rapid and reliable prescreening and early risk stratification of postoperative meningitis (PNM) remain challenging because clinical symptoms are nonsp...

Automated model-based lesion tracking in CT: colorectal liver metastases as a use case for development and performance analysis.

OBJECTIVE: To develop and evaluate an automated CT liver lesion-tracking algorithm that matches lesions over time, detects new metastases, and reports...

Radiographers' accuracy in interpreting acute musculoskeletal X-rays when supported by artificial intelligence - A multi-site cross-sectional study.

INTRODUCTION: The artificial intelligence (AI) tool BoneView™ has been introduced into clinical practice to support skeletal X-ray interpretation. Thi...

Microbiome-based control of postharvest mycotoxin-producing fungi in cereals.

Mycotoxin contamination caused by fungal pathogens remains a persistent threat to global food security, while the long-standing reliance on synthetic ...

Developmental neurotoxic effects of organophosphate flame retardants (OPFRs) across different life stages and the central role of pioneer transcription factors Neurog2/Ascl1 during the embryonic period.

In contemporary consumer products markets, organophosphorus flame retardants (OPFRs) are widely used, associated with non-carcinogenic health risks an...

A unified multi-modal foundation model for end-to-end emergency care.

Against the backdrop of population aging and the rising burden of chronic diseases in China, emergency departments (EDs) in tertiary hospitals remain ...

An interpretable machine learning model for early prediction of ESBL-producing bacteraemia in the emergency department.

Empirical antibiotic therapy in the emergency department (ED) is often initiated before susceptibility results are available, risking treatment failur...

Integration of metabolomics and machine learning algorithm for discovery of early diagnostic biomarkers of osteoporosis.

BACKGROUND: Osteoporosis (OP) is a prevalent metabolic bone disorder and a major public health concern characterized by reduced bone mass and bone mic...

AI-based organ weight estimation from postmortem computed tomography.

Accurate organ weight determination is essential in forensic autopsy. Postmortem computed tomography (CT) combined with Artificial Intelligence (AI)-b...

Artificial intelligence meets pediatric orthopedics: A comparative analysis of ChatGPT-4o, Gemini 2.0, and Claude 3.5 in detecting supracondylar humeral fractures.

BACKGROUND: Supracondylar humeral fractures constitute 10-16% of pediatric skeletal injuries, requiring timely diagnosis to prevent neurovascular comp...