Original Article

Published: Jun 24, 2026 | DOI: 10.24911/SJEMed.12-2914

The use of artificial intelligence in diagnosing emergency cases: a crosssectional study of physicians’ perspectives on the effectiveness of AI systems in improving diagnostic accuracy and reducing time to diagnosis


Authors: Sara S Al-Zahrani ORCID logo , Abdulrahman Mohammed Alkhuzaee ORCID logo , Mamdouh Saeedan Alqurashi ORCID logo , Jana Osama Ghazi ORCID logo , Majed Ahmad Dowayd ORCID logo , Sulafah Reda Namangani ORCID logo , Rahaf Khalid Bashamakh , Nawaf Hussain Aljafari ORCID logo , Mohammed Abu Aish


Abstract

Background: Artificial intelligence (AI) has the potential to improve diagnosis accuracy and speed in emergency rooms; yet, its acceptance and use by emergency physicians in Saudi Arabia remain limited.
Methods: A descriptive cross-sectional survey was issued to emergency physicians in Saudi Arabia. The questionnaire looked at demographics, AI exposure, perceived benefits and problems, and overall views toward AI. The data were evaluated with descriptive statistics, chi-square tests, ANOVA, and logistic regression.
Results: A total of 352 physicians participated, the majority of whom were young residents. Only 11.6% said they used AI on a regular basis. The majority of physicians (65.3%) had a negative attitude, whereas 6.8% were optimistic. Consultants had more favorable perceptions than residents. Attitudes differed considerably by region, age, gender, country, and professional level (p < 0.05). Key perceived benefits included increased diagnostic accuracy and speedier decision-making, while major hurdles included a lack of training, system inaccuracy, and difficulties interpreting AI outputs. Male and non-Saudi physicians had higher positive sentiments.
Conclusion: Despite acknowledging AI›s potential, practical adoption in emergency contexts remains low due to poor training and dependability issues. Structured AI training and system development are required to ensure a safe and effective integration into emergency practice.


Keywords: Artificial intelligence, emergency department, diagnostic accuracy, decision-making, triage, clinical practice, healthcare technology, AI in medicine.



Pubmed Style

Sara S Al-Zahrani, Abdulrahman Mohammed Alkhuzaee , Mamdouh Saeedan Alqurashi, Jana Osama Ghazi , Majed Ahmad Dowayd, Sulafah Reda Namangani, Rahaf Khalid Bashamakh, Nawaf Hussain Aljafari, Mohammed Abu Aish. The use of artificial intelligence in diagnosing emergency cases: a crosssectional study of physicians&rsquo; perspectives on the effectiveness of AI systems in improving diagnostic accuracy and reducing time to diagnosis. SJE Med. 2026; 24 (June 2026): -. doi:10.24911/SJEMed.12-2914

Publication History

Received: December 08, 2025

Accepted: January 19, 2026

Published: June 24, 2026


Authors

Sara S Al-Zahrani

Department of Medicine, College of Medicine, Umm AlQura University, Mecca, Saudi Arabia.

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Abdulrahman Mohammed Alkhuzaee

Department of Medicine, College of Medicine, Umm AlQura University, Mecca, Saudi Arabia.

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Mamdouh Saeedan Alqurashi

Department of Medicine, College of Medicine, Umm AlQura University, Mecca, Saudi Arabia.

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Jana Osama Ghazi

Department of Medicine, College of Medicine, Umm AlQura University, Mecca, Saudi Arabia.

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Majed Ahmad Dowayd

Department of Medicine, College of Medicine, Umm AlQura University, Mecca, Saudi Arabia.

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Sulafah Reda Namangani

Department of Medicine, College of Medicine, Umm AlQura University, Mecca, Saudi Arabia.

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Rahaf Khalid Bashamakh

College of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.

Nawaf Hussain Aljafari

Department of Medicine, College of Medicine, Umm AlQura University, Mecca, Saudi Arabia.

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Mohammed Abu Aish

Assistant Professor, Department of Pediatrics, Umm AlQura University Makkah, Makkah, Saudi Arabia.