Emergency Medicine

Distributed Precision Stroke Care: Artificial Intelligence-Driven Stroke Management Using Multimodal Sensor Data.

Delays in stroke diagnosis contribute to long-term disability. Many patients still face barriers to effective risk factor management, timely detection, and access to poststroke rehabilitation. The emergence of artificial intelligence-enabled, consumer-facing health technologies offers a transformative opportunity to address these gaps across the stroke care continuum. This review examines the evol...

Augmenting decision making in acute care surgery: A systematic review of machine learning-driven risk prediction models.

BACKGROUND: Acute care surgery (ACS) involves rapid, high-stakes decisions with limited opportunity for preoperative planning. While machine learning (ML) may improve risk prediction and decision making in this setting, its development, validation, and implementation in ACS remain understudied. We therefore evaluated the techniques, predictor features, and outcomes used in ML-driven risk predictio...

Performance of machine learning algorithms in predicting the need for surgical fixation in pediatric craniomaxillofacial trauma.

Machine learning offers a novel approach to improve surgical triage in pediatric craniomaxillofacial trauma, where decision-making often relies on cli...

Evaluating bone density with ultrasonic backscatter: Leveraging time-frequency analyses and convolutional neural networks.

Osteoporosis is a disease characterized by decreased bone density and increased fracture risk. This study proposes a convolutional neural network (CNN...

Sysmex Cell Population Data for Diagnosing Infection in Patients With Suspected Sepsis in the Emergency Department.

OBJECTIVES: Early diagnosis of suspected sepsis is crucial to improve patient survival. Cell population (CP) data, a set of leucocyte research paramet...

CEVG-RTNet: A real-time architecture for robust forest fire smoke detection in complex environments.

Forest fire smoke detection is crucial for early warning and emergency management, especially under complex environmental conditions such as low contr...

The Performance of Artificial Intelligence in Providing Real-Time Aid in Emergency Dental Trauma: A Clinical Validation Study.

BACKGROUND: Searching online for dental emergency treatment as a non-expert can lead to unreliable guidance. We tested the publicly available first mu...

Deep learning advances high-throughput toxicity screening of chemicals at multi-biological levels.

Deep learning (DL) has emerged as a powerful tool for modeling unstructured data, thereby improving prediction accuracy and expanding the application ...

Septic shock: Past, present, and perspectives.

Septic shock remains one of the most severe complications of infection, defined by circulatory, cellular, and metabolic dysfunction and associated wit...

Current State-of-the-Art 3D MRI Sequences for Assessing Bone Morphology with Emphasis on Cranial and Spinal Imaging: A Narrative Review.

Traditionally, CT has been the go-to method for visualizing bone structures, while MRI has been preferred for assessing soft tissues, because structur...

Smart Hospital Infrastructure: Enhancing Parking Management and Ambulance Accessibility in Urban Healthcare Systems.

Hospitals face significant challenges in parking management and assessing ambulances due to fast-growing urbanization, high population density, and tr...

Elucidating anti-triple-negative breast cancer mechanisms and mitigating toxicity of Fritillaria thunbergii Miq.: A multi-omics and network pharmacology approach.

ETHNOPHARMACOLOGICAL RELEVANCE: Fritillaria thunbergii Miq. (Zhebeimu, ZBM) is traditionally recognized in Chinese medicine for its effects of clearin...

Toward Standardized ICU Trauma Resuscitation via Markov Decision Processes.

OBJECTIVE: Guideline-based recommendations for posthemostasis resuscitation in trauma patients remain limited. This study aimed to define an interpret...

Real-Time Super-Resolution Ultrasound Imaging for Monitoring Tumor Response During Intensive Care Management of Oncologic Emergencies.

BACKGROUND: Oncologic emergencies in critically ill cancer patients frequently require rapid, real-time assessment of tumor responses to therapeutic i...

Expandable, But at What Cost? Failure Patterns in Corpectomy Cages From 373 Real-World Adverse Events.

STUDY DESIGN: Cross-sectional study. OBJECTIVE: This study aimed to analyze the failure patterns of expandable corpectomy cages. SUMMARY OF BACKGROUND...

Comparison of the Diagnostic Utility of Computed Tomography Angiography Head With and Without 3-Dimensional Volume-Rendered Images for Aneurysm Detection in Subarachnoid Hemorrhage Patients Versus Digital Subtraction Angiography.

BACKGROUND AND OBJECTIVES: Generating computed tomography (CT) angiography (CTA) 3-dimensional (3D) volume-rendered (3DVR) images can be time consumin...

An interpretable machine learning approach to evaluate 30-day mortality risk in patients with community-onset bacteremia.

BACKGROUND: Machine learning (ML) techniques are increasingly being used in health outcome research to develop predictive models. However, ML models a...

Identification of key genes in intracranial aneurysm via WGCNA: insights into immune microenvironment and therapeutic targets.

BACKGROUND: Intracranial aneurysms (IA) are prevalent vascular lesions whose rupture causes subarachnoid hemorrhage with high disability and mortality...

Evaluating the diagnostic accuracy of AI in ischemic and hemorrhagic stroke: A comprehensive meta-analysis.

Stroke poses a significant health challenge, with ischemic and hemorrhagic subtypes requiring timely and accurate diagnosis for effective management. ...

Are Artificial Intelligence Models Reliable for Clinical Application in Pediatric Fracture Detection on Radiographs? A Systematic Review and Meta-analysis.

BACKGROUND: Artificial intelligence (AI) applications for pediatric fracture diagnosis using radiographs have demonstrated growing potential in clinic...