Emergency Medicine

Combining transvaginal ultrasound radiomics with clinical-ultrasound semantic features for the identification of high-risk endometrial lesions.

OBJECTIVE: Preoperative risk stratification of high-risk endometrial lesions remains a clinical challenge. This study aimed to preliminarily explore an integrated machine learning approach combining transvaginal ultrasound (TVUS) radiomics, clinical indicators, and ultrasound semantic attributes to assist in clinical triage. METHODS: TVUS images (n = 956) from 239 patients were retrospectively ana...

A feature-efficient dual-task machine learning framework for predicting bone mineral density and osteoporosis stratification in resource-constrained environments.

Osteoporosis is a chronic skeletal disorder characterized by progressive bone mineral density (BMD) loss and structural deterioration, significantly increasing fracture risk. Despite its high prevalence, early detection remains challenging due to its asymptomatic progression and the limitations of conventional diagnostic techniques, such as Dual-Energy X-ray Absorptiometry (DXA). While DXA remains...

[Overview and conclusions of the STROKE data platform of the National Laboratory for Translational Neuroscience and the associated clinical studies].

Acute ischemic and hemorrhagic stroke are among the leading causes of mortality and long-term disability worldwide. In addition to the results of rand...

Multi-omics and network toxicology prioritize ADAMTS13 as a candidate gene computationally linked to TDCPP targets in hepatocellular carcinoma.

BACKGROUND: Tris(1,3-dichloro-2-propyl) phosphate (TDCPP), a widely used organophosphate flame retardant, has been increasingly recognized as a potent...

Integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma.

BACKGROUND: Epidemiological studies link long-term air pollution to an increased risk of hepatocellular carcinoma (HCC), but the underlying toxicologi...

Soft skills as mediation competencies in digitally mediated healthcare.

Digital transformation is reshaping healthcare delivery, with growing but uneven incorporation of artificial intelligence into clinical practice. Whil...

Teaching in the trenches: adaptive strategies for clinical education in crowded emergency departments.

Emergency department crowding has become a pervasive global challenge that strains patient flow and compromises clinical learning environments. Tradit...

Single cell and bulk transcriptomics reveal metabolic reprogramming biomarker signatures during extracorporeal membrane oxygenation for cardiogenic shock.

Cardiogenic shock (CS) patients receiving extracorporeal membrane oxygenation (ECMO) exhibit profound immune and metabolic disturbances, which may inf...

Diagnostic performance of an artificial intelligence algorithm for detecting pneumoperitoneum on abdominal CT scans.

OBJECTIVES: This study aims to evaluate the diagnostic performance of an artificial intelligence (AI) algorithm for detection, segmentation, and volum...

Impact of Artificial Intelligence Assistance on Diagnosing Traumatic Pneumothorax: A Comparison of Specialist and Non-Specialist Emergency Physicians.

INTRODUCTION: Supine chest radiography is routinely used in trauma care; however, its sensitivity is limited in pneumothorax detection. Although artif...

Methodological quality and performance of artificial intelligence and machine learning models for preoperative risk prediction in plastic surgery: A systematic review.

Artificial intelligence (AI) and machine learning (ML) are increasingly being applied to preoperative risk prediction in plastic surgery; however, the...

Public evaluations of AI-mediated healthcare when considering people with diverse access and support needs: a mixed-methods survey.

BACKGROUND: Artificial intelligence (AI) is increasingly being introduced into healthcare, including patient communication, monitoring, triage, decisi...

The Science of Preventing Delirium: Trends, Knowledge Gaps, and Future Directions Revealed Through Bibliometric Insights.

PURPOSE: To examine global research trends in delirium prevention through a bibliometric analysis and provide a structured overview of its development...

Mapping the knowledge landscape of planarian regeneration: a century of bibliometric insights.

BACKGROUND: Despite over two centuries of research, the knowledge landscape of planarian regeneration-a pivotal model for stem cell biology and regene...

Real-world multimetric comparison of four commercial artificial intelligence solutions for intracranial hemorrhage detection.

PURPOSE: To evaluate the real-world multimetric performance of four commercially available computed tomography (CT)-based artificial intelligence (AI)...

Computer-Vision Approach to Triaging Patient-Submitted Photos of Intestinal Ostomies.

BACKGROUND: Surgeons and ostomy nurses receive a high volume of stoma photos from patients. OBJECTIVE: This study aimed to develop and validate an aut...

Automated quality assurance for emergency department documentation: pilot comparison with physician peer review of simulated chest pain cases.

OBJECTIVES: To evaluate the feasibility and reliability of an artificial intelligence-driven quality assurance system for emergency chest pain documen...

Machine learning-supported cross-excitation laser-induced fluorescence lidar for the classification of oil spill.

Accurate identification of the spilled oil type was crucial for implementing suitable emergency response measures and guiding further marine oil pollu...

Enhancing the golden hour: classification of traumatic brain injury, severity, and concomitant clinical phenotypes using prehospital continuous physiological data during air transport.

During emergency transport, clinical assessment and vital signs may lack the sensitivity to identify traumatic brain injury (TBI) and identify specifi...

An explainable real-time artificial intelligence -assisted system to reduce intradialytic hypotension.

BACKGROUND: Intradialytic hypotension (IDH) is a frequent complication in hemodialysis and is associated with adverse cardiovascular and neurological ...