Developing, purchasing, implementing and monitoring AI tools in radiology: practical considerations. A multi-society statement from the ACR, CAR, ESR, RANZCR & RSNA

被引:37
作者
Brady, Adrian P. [1 ]
Allen, Bibb [2 ,3 ]
Chong, Jaron [4 ]
Kotter, Elmar [5 ]
Kottler, Nina [6 ,7 ]
Mongan, John [8 ]
Oakden-Rayner, Lauren [9 ]
dos Santos, Daniel Pinto [10 ,11 ]
Tang, An [12 ]
Wald, Christoph [13 ,14 ,15 ]
Slavotinek, John [16 ,17 ]
机构
[1] Univ Coll Cork, Cork, Ireland
[2] Grandview Med Ctr, Dept Radiol, Birmingham, AL USA
[3] Amer Coll Radiol, Data Sci Inst, Reston, VA USA
[4] Western Univ, Schulich Sch Med & Dent, Dept Med Imaging, London, ON, Canada
[5] Univ Freiburg, Fac Med, Med Ctr, Dept Diagnost & Intervent Radiol, Freiburg, Germany
[6] Radiol Partners, El Segundo, CA USA
[7] Stanford Ctr Artificial Intelligence Med & Imaging, Palo Alto, CA USA
[8] Univ Calif San Francisco, Dept Radiol & Biomed Imaging, San Francisco, CA USA
[9] Univ Adelaide, Australian Inst Machine Learning, Adelaide, SA, Australia
[10] Univ Hosp Cologne, Dept Radiol, Cologne, Germany
[11] Univ Hosp Frankfurt, Dept Radiol, Frankfurt, Germany
[12] Univ Montreal, Dept Radiol Radiat Oncol & Nucl Med, Montreal, PQ, Canada
[13] Lahey Hosp & Med Ctr, Dept Radiol, Burlington, MA USA
[14] Tufts Univ, Sch Med, Boston, MA USA
[15] Amer Coll Radiol, Board Chancellors, Reston, VA USA
[16] Flinders Med Ctr, South Australia Med Imaging, Adelaide, SA, Australia
[17] Flinders Univ S Australia, Coll Med & Publ Hlth, Adelaide, Australia
关键词
Artificial Intelligence; Radiology; Automation; Machine learning; ARTIFICIAL-INTELLIGENCE; SYSTEM; DIAGNOSIS; ETHICS;
D O I
10.1186/s13244-023-01541-3
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing diagnosis, quantification, and management of multiple medical conditions. Nevertheless, the ever-growing availability of AI tools in radiology highlights an increasing need to critically evaluate claims for its utility and to differentiate safe product offerings from potentially harmful, or fundamentally unhelpful ones.This multi-society paper, presenting the views of Radiology Societies in the USA, Canada, Europe, Australia, and New Zealand, defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiological practice. In addition to delineating the main points of concern that developers, regulators, and purchasers of AI tools should consider prior to their introduction into clinical practice, this statement also suggests methods to monitor their stability and safety in clinical use, and their suitability for possible autonomous function. This statement is intended to serve as a useful summary of the practical issues which should be considered by all parties involved in the development of radiology AI resources, and their implementation as clinical tools.Key points center dot The incorporation of artificial intelligence (AI) in radiological practice demands increased monitoring of its utility and safety.center dot Cooperation between developers, clinicians, and regulators will allow all involved to address ethical issues and monitor AI performance.center dot AI can fulfil its promise to advance patient well-being if all steps from development to integration in healthcare are rigorously evaluated.
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页数:19
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