Demystifying Medico-legal Challenges of Artificial Intelligence Applications in Molecular Imaging and Therapy

Mezrich, Jonathan L.

doi:10.1016/j.cpet.2021.08.002

Cited by 11 publications

(24 citation statements)

References 12 publications

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“…Current tort laws are not yet matured and Mezrich advises all clinicians including radiologists and non-radiologists to remain abreast to developments as they arise in this rapidly evolving area. 14 Patient data privacy remains as another dilemma in integrating AI into radiology reporting. The nonradiologist respondents did not feel as comfortable with privacy and security in the AI model of reporting compared to the current radiologist model, although most were supportive of providing consent for AI companies to utilise their patients' data for technology optimisation.…”

Section: Discussionmentioning

confidence: 99%

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Non‐radiologist perception of the use of artificial intelligence (AI) in diagnostic medical imaging reports

et al. 2022

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Introduction: Incorporating artificial intelligence (AI) in diagnostic medical imaging reports has the potential to improve efficiency. Although perception of radiologists, radiographers, medical students and patients on AI use in image reporting has been explored, there is limited literature on nonradiologist clinicians' opinion on this topic. Method: Single-centre online survey targeting non-radiologist medical staff conducted from May to August 2021 at a tertiary referral hospital in Melbourne, Australia. Survey questions revolved around clinicians' level of comfort acting on AI-generated reports with varying levels of radiologist involvement and scan complexity, opinion on medicolegal responsibility for erroneous AI-issued reports and perception of data privacy and security. Results: Eighty-eight responses were collected, including 47.9% of consultants. Non-radiologist clinicians across all seniorities and specialties felt significantly less comfortable acting on AI-issued reports compared with radiologist-issued reports (mean comfort radiologist 6.44/7, mean comfort AI 3.35/7, P < 0.001) but felt equally comfortable with an AI-hybrid model of care (mean comfort hybrid 6.38/7, P = 0.676). Non-radiologist clinicians believed that medicolegal responsibility with errors in AI-issued reports mostly lay with hospitals or health service providers (65.9%) and radiologists (54.5%). Regarding data privacy and security, non-radiologist clinicians felt significantly less comfortable with AI issuing image reports instead of radiologists (P < 0.001). Conclusion: A hybrid AI-generated radiologist-confirmed method of image reporting may be the ideal way of integrating AI into clinical practice based on the perception of our referring non-radiologist medical colleagues. Formal guidelines on medicolegal responsibility and data privacy should be established prior to utilising AI in the clinical setting.

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Section: Discussionmentioning

confidence: 99%

“…These assume that the referring physician, if obviating the use of a radiologist, discloses the risks to the patient. Current tort laws are not yet matured and Mezrich advises all clinicians including radiologists and non‐radiologists to remain abreast to developments as they arise in this rapidly evolving area 14 …”

Section: Discussionmentioning

confidence: 99%

Non‐radiologist perception of the use of artificial intelligence (AI) in diagnostic medical imaging reports

et al. 2022

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“…Furthermore, excessive workload and understaffing in healthcare environments can add to work-related stressors and possibly lead to burnout, whereas maintaining an adequate supply of physicians is vital to a well-functioning healthcare system. Fostering innovation in radiology departments (such as the widespread adoption of radiological structured reporting, the use of validated AI systems to assist radiologists’ activity, the implementation of optimal ergonomics, and the constructive use of social media) can also play a role in preventing burnout by optimizing workflow and improving overall work quality [ 77 , 78 , 81 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 ].…”

Section: Discussionmentioning

confidence: 99%

Exploring Radiologists’ Burnout in the COVID-19 Era: A Narrative Review

Gabelloni

Faggioni

Fusco

et al. 2023

IJERPH

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Since its beginning in March 2020, the COVID-19 pandemic has claimed an exceptionally high number of victims and brought significant disruption to the personal and professional lives of millions of people worldwide. Among medical specialists, radiologists have found themselves at the forefront of the crisis due to the pivotal role of imaging in the diagnostic and interventional management of COVID-19 pneumonia and its complications. Because of the disruptive changes related to the COVID-19 outbreak, a proportion of radiologists have faced burnout to several degrees, resulting in detrimental effects on their working activities and overall wellbeing. This paper aims to provide an overview of the literature exploring the issue of radiologists’ burnout in the COVID-19 era.

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“…Early development efforts can pose more risk to developers and consumers. In order to address the concerns related to liability, there have been successful programs in other industries to encourage adoption of new technology and support consumer protection such as for vaccines and autonomous vehicles (29).…”

Section: Sustainability Of Societal Wellbeingmentioning

confidence: 99%

“…There is limited legal precedent for the use or misuse of AI in healthcare and it is even unclear whether product liability law would apply to AI software in medicine, particularly if the software changes over time after regulatory approval (29). At present, we believe that all AI in nuclear medicine must be supervised by a physician and that patient care choices can be informed by AI, but ultimately are made by the physician based on all data and the doctor/patient relationship.…”

Section: Regulatory and Legal Aspectsmentioning

confidence: 99%

Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem

Saboury

Bradshaw

Boellaard³

et al. 2022

J Nucl Med

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Demystifying Medico-legal Challenges of Artificial Intelligence Applications in Molecular Imaging and Therapy

Cited by 11 publications

References 12 publications

Non‐radiologist perception of the use of artificial intelligence (AI) in diagnostic medical imaging reports

Non‐radiologist perception of the use of artificial intelligence (AI) in diagnostic medical imaging reports

Exploring Radiologists’ Burnout in the COVID-19 Era: A Narrative Review

Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem

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