Achour Nebil, Zapata Tomas, Saleh Yousef, Pierscionek Barbara, Azzopardi-Muscat Natasha, Novillo-Ortiz David, Morgan Cathal, Chaouali Mafaten
Faculty of Health, Medicine and Social Care, Anglia Ruskin University, Cambridge, UK.
World Health Organization Regional Office for Europe, Copenhagen, Denmark.
Health Technol (Berl). 2025;15(3):489-501. doi: 10.1007/s12553-025-00970-y. Epub 2025 Apr 25.
PURPOSE: This study aims to explore the application of Artificial intelligence (AI) systems in radiology departments and the role they play in the shortage of radiologists. It examines the ethical and legal considerations for uptake of AI both in relation to patient safety and for the profession of radiology. METHODS: A systematised review was selected for this research study to collect maximum relevant evidence that provides a comprehensive overview of AI application in radiology specifically in terms of addressing radiologist shortages in hospitals. The search was complemented by grey literature to fill potential gaps. RESULTS: Findings suggest that AI can read and interpret images more effectively and faster than radiologists and that it could be more widely used to reduce the impact of the global radiologist shortage, leading to better patient outcomes and safety. However, there are potential challenges predominantly ethical and legal. Concerns over complete radiologist replacement by AI do not currently seem likely, but rather the use of AI to complement radiologists in their work. CONCLUSIONS: AI cannot replace radiologists, instead radiology services will need the input of radiologists, AI systems and radiographers to provide a safe healthcare for all patients, therefore they are complementary. Radiologist jobs will most probably change to reduce repetitive tasks that can be conducted by AI. Radiologists and radiographers play a role in the provision of quality care in both normal day-to-day events and during times of disaster. Their role in diagnosing and prognosing diseases provides guidance during preparedness, response and recovery.
目的:本研究旨在探讨人工智能(AI)系统在放射科的应用及其在放射科医生短缺问题中所起的作用。它审视了在患者安全及放射学专业方面采用人工智能时的伦理和法律考量。 方法:本研究选用了系统评价,以收集最多的相关证据,全面概述人工智能在放射学中的应用,特别是在解决医院放射科医生短缺方面。通过灰色文献补充搜索,以填补潜在空白。 结果:研究结果表明,人工智能比放射科医生能更有效、更快地读取和解读图像,并且可以更广泛地用于减少全球放射科医生短缺的影响,从而带来更好的患者治疗效果和安全性。然而,存在一些潜在挑战,主要是伦理和法律方面的。目前看来,人工智能完全取代放射科医生的担忧不太可能发生,而是利用人工智能来辅助放射科医生工作。 结论:人工智能无法取代放射科医生,相反,放射学服务需要放射科医生、人工智能系统和放射技师的共同参与,以便为所有患者提供安全的医疗保健,因此它们是互补的。放射科医生的工作很可能会发生变化,以减少可由人工智能执行的重复性任务。放射科医生和放射技师在日常正常情况下以及灾难期间提供优质护理方面都发挥着作用。他们在疾病诊断和预后方面的作用在备灾、应对和恢复过程中提供指导。
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