AI Medical Compendium Journal:
Annals of emergency medicine

Showing 1 to 10 of 31 articles

Development of Clinically Validated Artificial Intelligence Model for Detecting ST-segment Elevation Myocardial Infarction.

Annals of emergency medicine
STUDY OBJECTIVE: Although the importance of primary percutaneous coronary intervention has been emphasized for ST-segment elevation myocardial infarction (STEMI), the appropriateness of the cardiac catheterization laboratory activation remains subopt...

Rapid Electroencephalography and Artificial Intelligence in the Detection and Management of Nonconvulsive Seizures.

Annals of emergency medicine
STUDY OBJECTIVE: Nonconvulsive status epilepticus is a commonly overlooked cause of altered mental status. This study assessed nonconvulsive status epilepticus prevalence in emergency department (ED) patients with acute neurologic presentations using...

The AI Future of Emergency Medicine.

Annals of emergency medicine
In the coming years, artificial intelligence (AI) and machine learning will likely give rise to profound changes in the field of emergency medicine, and medicine more broadly. This article discusses these anticipated changes in terms of 3 overlapping...

Harnessing the Power of Generative AI for Clinical Summaries: Perspectives From Emergency Physicians.

Annals of emergency medicine
STUDY OBJECTIVE: The workload of clinical documentation contributes to health care costs and professional burnout. The advent of generative artificial intelligence language models presents a promising solution. The perspective of clinicians may contr...

Development and Validation of a Natural Language Processing Model to Identify Low-Risk Pulmonary Embolism in Real Time to Facilitate Safe Outpatient Management.

Annals of emergency medicine
STUDY OBJECTIVE: This study aimed to (1) develop and validate a natural language processing model to identify the presence of pulmonary embolism (PE) based on real-time radiology reports and (2) identify low-risk PE patients based on previously valid...

Evaluating the Reliability of a Remote Acuity Prediction Tool in a Canadian Academic Emergency Department.

Annals of emergency medicine
STUDY OBJECTIVE: There is increasing interest in harnessing artificial intelligence to virtually triage patients seeking care. The objective was to examine the reliability of a virtual machine learning algorithm to remotely predict acuity scores for ...