AIMC Topic: Emergency Service, Hospital

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AI-ECG Supported Decision-Making for Coronary Angiography in Acute Chest Pain: The QCG-AID Study.

Journal of Korean medical science
This pilot study evaluates an artificial intelligence (AI)-assisted electrocardiography (ECG) analysis system, QCG, to enhance urgent coronary angiography (CAG) decision-making for acute chest pain in the emergency department (ED). We retrospectively...

Evaluating a large language model's accuracy in chest X-ray interpretation for acute thoracic conditions.

The American journal of emergency medicine
BACKGROUND: The rapid advancement of artificial intelligence (AI) has great ability to impact healthcare. Chest X-rays are essential for diagnosing acute thoracic conditions in the emergency department (ED), but interpretation delays due to radiologi...

Constructing an early warning model for elderly sepsis patients based on machine learning.

Scientific reports
Sepsis is a serious threat to human life. Early prediction of high-risk populations for sepsis is necessary especially in elderly patients. Artificial intelligence shows benefits in early warning. The aim of the study was to construct an early machin...

Preliminary evaluation of ChatGPT model iterations in emergency department diagnostics.

Scientific reports
Large language model chatbots such as ChatGPT have shown the potential in assisting health professionals in emergency departments (EDs). However, the diagnostic accuracy of newer ChatGPT models remains unclear. This retrospective study evaluated the ...

Artificial Intelligence and Qualitative Analysis of Emergency Department Telemental Health Care Implementation Survey.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
: Implementation of telemental health care in emergency departments (EDs) in the United States (U.S.) has been increasing. Artificial intelligence (AI) can augment traditional qualitative research methods; little is known about its efficiency and acc...

Artificial intelligence versus orthopedic surgeons as an orthopedic consultant in the emergency department.

Injury
INTRODUCTION: ChatGPT, a widely accessible AI program, has demonstrated potential in various healthcare applications, including emergency department (ED) triage, differential diagnosis, and patient education. However, its potential in providing recom...

Interpretable machine learning models for prolonged Emergency Department wait time prediction.

BMC health services research
OBJECTIVE: Prolonged Emergency Department (ED) wait times lead to diminished healthcare quality. Utilizing machine learning (ML) to predict patient wait times could aid in ED operational management. Our aim is to perform a comprehensive analysis of M...

Compliance Evaluation with ChatGPT for Diagnosis and Treatment in Patients Brought to the ED with a Preliminary Diagnosis of Stroke.

Prehospital emergency care
OBJECTIVES: Chat Generative Pre-trained Transformer (ChatGPT) is a natural language processing product developed by OpenAI. Recently, the use of ChatGPT has gained attention in the field of health care, particularly for its potential applications in ...

Forecasting trends of rising emergency department chest imaging using machine learning.

Emergency radiology
INTRODUCTION: Imaging studies in the acute care setting, such as the emergency room, have been increasing. In this report, we use the Centers for Medicare and Medicaid services (CMS) database to assess trends in ED chest CT and chest CTA imaging in E...

Deep Learning-Based Electrocardiogram Model (EIANet) to Predict Emergency Department Cardiac Arrest: Development and External Validation Study.

Journal of medical Internet research
BACKGROUND: In-hospital cardiac arrest (IHCA) is a severe and sudden medical emergency that is characterized by the abrupt cessation of circulatory function, leading to death or irreversible organ damage if not addressed immediately. Emergency depart...