Emergency Medicine

Automated Shoulder Radiograph Quality Review to Support Efficient Workflow in the Emergency Department: The SQUIRE Deep Learning Ensemble.

Suboptimal shoulder radiographs are a persistent challenge, leading to unnecessary radiation exposure, workflow delays, and increased costs from repeat imaging. Repeat imaging is most often required due to anatomy cutoff or suboptimal patient positioning, underscoring the need for targeted feedback and decision-support tools to improve image acquisition consistency. This study aimed to develop and...

Comment on "Integrated multi-Omics and network toxicology elucidate the multi-target mechanisms of environmental hormones in driving hepatocellular carcinoma".

Computational toxicology of N-nitrosamine impurities: from molecular structure to regulatory concern.

Since 2018, drug recalls and other regulatory actions related to impurities, particularly N-nitrosamines, have raised significant toxicological and pu...

The Synovial Fingerprint of Ankle Fractures: A Central Role for WNT Pathway Activation in Posttraumatic Ankle Osteoarthritis.

BACKGROUND: Osteoarthritis (OA) of the ankle is a disabling and understudied disease, most commonly emerging posttraumatically after ankle fractures (...

Harnessing Large Language Models in Neonatal IVH: Exploring RAG Methodology for Prognostic Variable Discovery.

OBJECTIVE: To evaluate whether large language models (LLMs) can autonomously synthesize existing literature and accurately extract prognostic variable...

The Silent Author: A Pilot Study Detecting AI-Assisted Writing in Plastic and Reconstructive Surgery Journals.

BACKGROUND: Academic publishing underpins surgical decision-making, but the rapid adoption of generative artificial intelligence (AI) raises concerns ...

The role of artificial intelligence in virtual emergency care: a systematic review.

BACKGROUND: The integration of artificial intelligence (AI) into virtual emergency care represents a potentially transformative approach to healthcare...

Recent advances in sex-specific reproductive microphysiological systems for the systematic evaluation of assisted reproductive technology.

The rising global burden of infertility continues to increase clinical reliance on assisted reproductive technology (ART), yet overall outcomes remain...

Deep learning-based segmentation of aneurysmal subarachnoid hemorrhage: toward accurate and scalable prognostic imaging.

BACKGROUND: Accurate segmentation of aneurysmal cerebral hemorrhages, including subarachnoid hemorrhage (SAH), intraparenchymal hemorrhage (IPH), and ...

Effect of PET-MPs exposure on the toxicology of PCOS: a multi-platform computational toxicology investigation.

Polyethylene terephthalate microplastics (PET-MPs) function as endocrine-disrupting agents that interfere with steroidogenesis and folliculogenesis, p...

Convolutional neural networks in paediatric fracture detection: pooled evidence from a systematic review and meta-analysis.

OBJECTIVE: The objective of this review was to systematically evaluate the diagnostic accuracy of artificial intelligence (AI) models for detecting pa...

Toxicologic Pathology Forum*: Virtual Staining of Nonclinical Study Slides-A Brief Review of the Current Status and Future Opportunities.

Virtual staining of unstained tissue for histologic assessment is the subject of burgeoning research and has been approached using various methodologi...

When seconds matter - introducing a surgical salvage strategy by emergency robotic surgery: a review.

Robotic surgery has expanded minimally invasive options but introduces specific vulnerabilities during intraoperative emergencies. The physical separa...

Advances in Imaging-Based Fracture Risk Assessment for Unlocking Latent Skeletal Fragility.

From "high AUC" to evidentiary reliability: audit-ready deployment standards for deep-learning rib-fracture detection in postmortem CT.

Prediction of femoral shaft fracture healing and clinical decision support through integration of mechano-biological modeling and machine learning.

BACKGROUND AND OBJECTIVES: Current clinical practice in preoperative planning for femoral shaft fractures lacks tools capable of quantitatively predic...

Prompt engineering enables open-source large language models to match proprietary models in diagnostic accuracy for annotation of radiology reports.

AIM: This study aimed to test whether open-source large language models (LLMs) can match the diagnostic accuracy of proprietary models in annotating t...

Clinical Informatics and Artificial Intelligence: What the Working Emergency Physician Needs to Know.

BACKGROUND: Clinical Informatics is wide-ranging field that engages with nearly every aspect of clinical care that is documented in the electronic hea...

Meta-analysis, WGCNA, and machine learning converge on a four-gene biomarker panel for heat stress tolerance in Solanum lycopersicum.

Heat stress severely compromises growth, reproduction, and yield in Solanum lycopersicum, necessitating the identification of reliable molecular bioma...

Machine learning-based models using preoperative imaging and clinical data to predict intraoperative rebleeding and functional recovery in intracerebral hemorrhage patients: a multicenter study.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is associated with high mortality and disability. This study aimed to develop and validate mach...