Latest AI and machine learning research in emergency medicine for healthcare professionals.
Triage errors, including undertriage and overtriage, are persistent challenges in emergency departments (EDs). With increasing patient influx and staff shortages, the integration of artificial intelligence (AI) into triage protocols has gained attention. This study compares the performance of three AI models [Natural Language Processing (NLP), Large Language Models (LLM), and Joint Embedding Pre...
The classification and analysis of coal are crucial for energy production and resource management. Shadowgraphy, leveraging variations in air refractive index and transmittance caused by shockwaves, presents a simple and accessible approach for the classification and component analysis of energetic materials. In this study, we developed an automated laser excitation and image acquisition system ut...
OBJECTIVE: Intracerebral hemorrhage (ICH) remains a critical neurosurgical emergency with high mortality and long-term disability. Despite advancement...
OBJECTIVE: Given that resection of brainstem cavernous malformations (BSCMs) ends hemorrhaging but carries a high risk of neurological deficits, it is...
Background: Chronic critical illness (CCI) is a serious condition characterized by a prolonged course of illness, resulting in elevated morbidity and ...
Background: Contrast-induced nephropathy (CIN) is a serious complication following acute coronary syndrome (ACS), leading to increased morbidity and m...
Background: Postoperative gastrointestinal (GI) dysfunction is a common complication following critical illness. The splanchnic circulation is sensiti...
Background : Heart rate variability (HRV) measures give insight into the autonomic regulation of cardiac function in healthy and critically ill patien...
Sepsis is a life-threatening disease caused by the dysregulation of the immune response. It is important to identify influential genes modulating the ...
BACKGROUND AND OBJECTIVES: Delays in septic shock diagnosis cause preventable mortality in children. Evidence is limited around early recognition stra...
New psychoactive substances (NPS) pose an increasing challenge for clinical and forensic toxicology due to the initial lack of analytical and metaboli...
Emergency responders face significant human factors and ergonomic (HF/E) challenges related to physical, cognitive, emotional, and training demands du...
Artificial intelligence (AI) has gained significant attention in various scientific fields due to its ability to process large datasets. In nuclear ra...
BACKGROUND: Clinical work-up for suspected cardiac chest pain is resource intensive. Despite expectations, high-sensitivity cardiac troponin assays ha...
BACKGROUND: Large language models (LLMs) have shown promise in various medical applications, but their potential as decision support tools in emergenc...
BACKGROUND: It is becoming increasingly important to evaluate the effectiveness of large language models (LLMs) and query-assisted platforms like Goog...
Accurate interpretation of multi-view radiographs is crucial for diagnosing fractures, muscular injuries, and other anomalies. While significant adv...
The international refugee crisis deepens, exposing millions of dis placed children to extreme psychological trauma. This research suggests a com pac...
Building damage identification shortly after a disaster is crucial for guiding emergency response and recovery efforts. Although optical satellite i...
Comorbidity networks, which capture disease-disease co-occurrence usually based on electronic health records, reveal structured patterns in how dise...