Abstract

This review summarizes current evidence on the impact of artificial intelligence and machine learning in triage, hospital admission decisions, and medical imaging within emergency departments. In triage, electronic systems and deep learning models outperform manual assessments in predicting the need for critical care and hospitalization. For admission decisions, natural language processing and neural network–based models enhance early capacity planning and optimize resource utilization. In medical imaging, deep learning applications accelerate the detection of urgent findings in computed tomography and radiography, improving diagnostic accuracy. Overall, artificial intelligence and machine learning based decision support systems have the potential to improve speed, accuracy, and patient safety in emergency care; multicenter prospective validation studies and integration into clinical workflows are essential for widespread implementation.

Keywords: artificial intelligence, machine learning, emergency department, triage, admission, intensive care, medical imaging, decision support system