ArticleFrontiers in public health2023
Perceptions and concerns of emergency medicine practitioners about artificial intelligence in emergency triage management during the pandemic: a national survey-based study.
Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Healthcare professionals' perspectives on artificial intelligence in patient care: a systematic review of hindering and facilitating factors on different levels.BMC health services research · 2025Pooled it
- Beyond awareness: Defining AI readiness in Emergency Medicine across health systems.African journal of emergency medicine : Revue africaine de la medecine d'urgence · 2026Article
- Perception and challenges of artificial intelligence (AI) in Emergency Medicine: A multi-country study in Sub-Saharan Africa.African journal of emergency medicine : Revue africaine de la medecine d'urgence · 2026Article
- Visual representation bias in artificial intelligence-generated depictions of anesthesia, pain, and intensive care professionals.The Journal of international medical research · 2026Article
- Building a Global Research Network for Fair, Accountable, Interpretable, and Responsible AI in Emergency Care: Protocol for a FAIR-EC Study.JMIR research protocols · 2026Article
- Artificial intelligence in the emergency department-- applications, perceptions and limitations: a narrative review.World journal of emergency medicine · 2026Review
- Advancing medical AI through benchmarking and competition for specialty triage.NPJ digital medicine · 2026Article
- Large Language Model-Assisted Point-in-Time Interpretation of Advanced Hemodynamics in Liver Transplant Recipients: A Pilot Evaluation of Content Quality and Safety.Journal of clinical medicine · 2026Article
- Ethical considerations of artificial intelligence in emergency medicine for triage and resource allocation: a scoping review.Clinical and experimental emergency medicine · 2025Article
- Prognostic significance of the Tpe/Qtc ratio in predicting major adverse cardiac events in acute STEMI patients.Scientific reports · 2025Article
- Evaluating large language models for renal colic imaging recommendations: a comparative analysis of Gemini, copilot, and ChatGPT-4.0.International journal of emergency medicine · 2025Article
- AI-assisted decision-making in mild traumatic brain injury.BMC emergency medicine · 2025Article
- Article
- Artificial intelligence in emergency department triage: perspective of human professionals.Frontiers in digital health · 2025Article
- Drinking from the Holy Grail-Does a Perfect Triage System Exist? And Where to Look for It?Journal of personalized medicine · 2024Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: There have been continuous discussions over the ethics of using AI in healthcare. We sought to identify the ethical issues and viewpoints of Turkish emergency care doctors about the use of AI during epidemic triage. Materials and methods: Ten emergency specialists were initially enlisted for this project, and their responses to open-ended questions about the ethical issues surrounding AI in the emergency room provided valuable information. A 15-question survey was created based on their input and was refined through a pilot test with 15 emergency specialty doctors. Following that, the updated survey was sent to emergency specialists via email, social media, and private email distribution. Results: 167 emergency medicine specialists participated in the study, with an average age of 38.22 years and 6.79 years of professional experience. The majority agreed that AI could benefit patients (54.50%) and healthcare professionals (70.06%) in emergency department triage during pandemics. Regarding responsibility, 63.47% believed in shared responsibility between emergency medicine specialists and AI manufacturers/programmers for complications. Additionally, 79.04% of participants agreed that the responsibility for complications in AI applications varies depending on the nature of the complication. Concerns about privacy were expressed by 20.36% regarding deep learning-based applications, while 61.68% believed that anonymity protected privacy. Additionally, 70.66% of participants believed that AI systems would be as sensitive as humans in terms of non-discrimination. Conclusion: The potential advantages of deploying AI programs in emergency department triage during pandemics for patients and healthcare providers were acknowledged by emergency medicine doctors in Turkey. Nevertheless, they expressed notable ethical concerns related to the responsibility and accountability aspects of utilizing AI systems in this context.
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