Emergency Medicine

LI-RADS-aligned artificial intelligence for liver cancer diagnosis: methods, evidence, and clinical readiness.

Liver tumor diagnosis relies heavily on imaging, and the liver imaging reporting and data system (LI-RADS) provides a structured framework for evaluating hepatocellular carcinoma (HCC) and related entities in at-risk populations. Artificial intelligence (AI) has rapidly expanded across CT, MRI, and ultrasound/CEUS, yet its clinical credibility depends on adherence to modality-appropriate tasks, ro...

Novel Psychoactive Substances: Slaying the Dragon With Artificial Intelligence.

BACKGROUND: The emergence of novel psychoactive substances (NPSs) has overwhelmed forensic, health care, and regulatory systems. Conventional analytical techniques are ineffective for identifying known compounds but fail against newly synthesized NPSs lacking reference standards. This review explores the roles of artificial intelligence (AI) and machine learning in addressing growing challenges in...

Increased Utilization of Telemedical Emergency and Nonurgent Care Following Deployment of Virtual Triage and Care Referral in Australia.

OBJECTIVE: To evaluate whether an artificial intelligence-based national virtual triage and care referral (VTCR) service in Australia improved care ac...

Acceptability of Using Artificial Intelligence in the National Health Service Breast Screening Program: A Randomized Online Survey of Screening-Eligible Women in England.

OBJECTIVE: To compare acceptability of 2 artificial intelligence (AI) use cases in the English National Health Servic Breast Screening Program. PATIEN...

An explainable predictive machine learning model reveals ARRB2 as a key gene in post-traumatic stress disorder: A GEO database study.

A number of processes and pathways have been reported in the development of Post-Traumatic Stress Disorder (PTSD), however, novel biomarkers need to b...

Development and Validation of an Automated Pipeline for the Detection of Monteggia Fracture Dislocations in Pediatric Radiographs.

BACKGROUND: Monteggia fractures are a complex elbow injury that can be missed in up to 50% of pediatric elbow injuries during initial radiographic ass...

Decipher the molecular network of PFOA in inflammatory bowel disease through integrating machine learning, molecular docking strategies, and validation in vitro.

OBJECTIVE: Perfluorooctanoic Acid (PFOA), widely recognized as an enduring environmental pollutant, is associated with immune system disruption and po...

Efficacy and comparative performance of machine learning models for stroke risk prediction in hypertensive patients: A systematic review and meta-analysis.

BACKGROUND: Stroke poses a significant health burden among hypertensive patients, where traditional risk models often lack precision. Machine learning...

Evaluating an Artificial Intelligence software for opportunistic low bone mineral density and osteoporosis screening: a validation study.

Despite the profound prevalence and fracture risk of osteoporosis, access to the gold standard DXA scans remains limited, especially in rural communit...

Generative artificial intelligence as a source of advice on resuscitation and first aid for laypeople: A scoping review.

INTRODUCTION: The performance of cutting-edge generative artificial intelligence (GenAI) in guiding laypeople on how to give help in health emergencie...

Predictive modeling of hospital emergency department demand using artificial intelligence: A systematic review.

BACKGROUND: Accurately forecasting patient arrivals in hospital emergency departments (EDs) is critical for hospital capacity and planning and clinica...

Aspartame promotes ovarian cancer progression: A multi-omics study integrating mendelian randomization, network toxicology, and in vitro validation.

The causal relationship between the artificial sweetener aspartame and ovarian cancer (OC), a highly lethal malignancy, remains unclear. This study, t...

Performance of ChatGPT versus spine surgeons as an emergency department spine call consultant.

BACKGROUND: Large language models (LLMs) like ChatGPT are increasingly being recognized as credible tools for use across diverse healthcare settings. ...

Industry 6.0 capabilities in orthopaedics: Towards hyper-personalized and autonomous surgical care.

BACKGROUND: Industry 6.0 represents the next frontier in technological evolution, integrating artificial intelligence (AI), autonomous robotics, digit...

Diagnosis of shoulder dislocation on AP radiographs: A comparative analysis of diagnostic performance between orthopedic surgeons, emergency physicians, and ChatGPT models.

OBJECTIVE: This study aimed to evaluate the diagnostic performance of ChatGPT in identifying acute shoulder dislocations and to compare its accuracy w...

Generative artificial intelligence provides accurate case selection in veterinary retrospective studies.

OBJECTIVE: To evaluate the agreement of automation tools with expert evaluators in identifying cases meeting inclusion and exclusion criteria for retr...

Modern integrative prostate cancer diagnostics.

PURPOSE OF REVIEW: To review contemporary applications, performance, and implementation challenges of artificial intelligence (AI) in the radiological...

Computer-vision based recognition of cervical spine stabilization during trauma resuscitation.

BACKGROUND: Cervical spine (c-spine) injuries can lead to significant disability and mortality. Although stabilization is the primary management for s...

Quantitative EEG enhances early assessment and prognostic stratification of brain dysfunction in infants with abusive head trauma.

AIM: To assess the value of quantitative EEG (qEEG) as a diagnostic and prognostic biomarker in infants with abusive head trauma (AHT). Despite its ce...

Deep learning for pediatric femoral neck fracture detection in a multicenter study.

Pediatric femoral neck fractures (FNFs) are uncommon but may result in severe complications if undiagnosed. This study developed a deep learning model...