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akaturk Akademik ölçüm

Makale detayı · 2025

Mapping artificial intelligence models in emergency medicine: A scoping review on artificial intelligence performance in emergency care and education

YÖKSİS OpenAlex Açık erişim · diamond SJR Q1 JCR Q1 TR Index Atıf 16 Üst %10 Yüzdelik 94.5% FWCI 4.34
Yıl
2025
Tür
article

Veri kaynağı ayrımı

  • YÖKSİS YÖKSİS makale kaydı
  • YÖKSİS dergi adı Turkish Journal of Emergency Medicine
  • Katalog eşleşmesi (ISSN) Turkish Journal of Emergency Medicine
  • OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)

Özet

OpenAlex · İngilizce

Artificial intelligence (AI) is increasingly improving the processes such as emergency patient care and emergency medicine education. This scoping review aims to map the use and performance of AI models in emergency medicine regarding AI concepts. The findings show that AI-based medical imaging systems provide disease detection with 85%-90% accuracy in imaging techniques such as X-ray and computed tomography scans. In addition, AI-supported triage systems were found to be successful in correctly classifying low- and high-urgency patients. In education, large language models have provided high accuracy rates in evaluating emergency medicine exams. However, there are still challenges in the integration of AI into clinical workflows and model generalization capacity. These findings demonstrate the potential of updated AI models, but larger-scale studies are still needed.

Konular

Atıflar

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16 atıf

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  1. Classification of Atelectasis from Chest X-Ray Images Using Deep Learning Approaches 2026 Atıf 0 · OpenAlex

Yazarlar

  1. GÖKSU BOZDERELİ BERİKOL ATILIM ÜNİVERSİTESİ
  2. ALTUĞ KANBAKAN UFUK ÜNİVERSİTESİ
  3. BUĞRA İLHAN KIRIKKALE ÜNİVERSİTESİ
  4. FATİH DOĞANAY