Impact of artificial intelligence on clinical radiography practice: Futuristic prospects in a low resource setting

Wuni, A.-R.; Botwe, Benard Ohene; Akudjedu, Theophilus N.

doi:10.1016/j.radi.2021.07.021

Cited by 22 publications

(15 citation statements)

References 31 publications

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“…While there was no change in respondents current understanding to their desired understanding of AI for those already expert, 40% of respondents indicated that their desired level of understanding was competent or better. Several reports have highlighted the importance of AI education in increasing its use, optimisation and implementation among medical imaging practitioners 11,13,14 . While AI education was broadly considered an essential part of the training of the medical imaging workforce, respondents were equally strong of the view that there is no need for patients or the general public to have that insight.…”

Section: Discussionmentioning

confidence: 99%

“…Several reports have highlighted the importance of AI education in increasing its use, optimisation and implementation among medical imaging practitioners. 11,13,14 While AI education was broadly considered an essential part of the training of the medical imaging workforce, respondents were equally strong of the view that there is no need for patients or the general public to have that insight. Of course, some insight is required among patient groups in order to adequately gain informed consent.…”

Section: Discussionmentioning

confidence: 99%

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Australian perspectives on artificial intelligence in medical imaging

Currie

Nelson

Hewis

et al. 2022

J of Medical Radiation Sci

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Introduction While artificial intelligence (AI) and recent developments in deep learning (DL) have sparked interest in medical imaging, there has been little commentary on the impact of AI on imaging technologists. The aim of this survey was to understand the attitudes, applications and concerns among nuclear medicine and radiography professionals in Australia with regard to the rapidly emerging applications of AI. Methods An anonymous online survey with invitation to participate was circulated to nuclear medicine and radiography members of the Rural Alliance in Nuclear Scintigraphy and the Australian Society of Medical Imaging and Radiation Therapy. The survey invitations were sent to members via email and as a push via social media with the survey open for 10 weeks. All information collected was anonymised and there is no disclosure of personal information as it was de‐identified from commencement. Results Among the 102 respondents, there was a high level of acceptance of lower order tasks (e.g. patient registration, triaging and dispensing) and less acceptance of high order task automation (e.g. surgery and interpretation). There was a low priority perception for the role of AI in higher order tasks (e.g. diagnosis, interpretation and decision making) and high priority for those applications that automate complex tasks (e.g. quantitation, segmentation, reconstruction) or improve image quality (e.g. dose / noise reduction and pseudo CT for attenuation correction). Medico‐legal, ethical, diversity and privacy issues posed moderate or high concern while there appeared to be no concern regarding AI being clinically useful and improving efficiency. Mild concerns included redundancy, training bias, transparency and validity. Conclusion Australian nuclear medicine technologists and radiographers recognise important applications of AI for assisting with repetitive tasks, performing less complex tasks and enhancing the quality of outputs in medical imaging. There are concerns relating to ethical aspects of algorithm development and implementation.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Australian perspectives on artificial intelligence in medical imaging

Currie

Nelson

Hewis

et al. 2022

J of Medical Radiation Sci

View full text Add to dashboard Cite

show abstract

“…It has been predicted that AI will change professions, roles will be reimagined, and more mechanistic tasks may be entirely replaced [6][7][8][9][10][11][12][13][14] . A negative depiction of AI in the media together with dichotomy of opinion regarding AI in the literature may influence the perceptions of clinicians and may impact the attractiveness of radiology as a career [5 , 17 , 18] .…”

Section: Reimagining the Future Of Radiography Roles With Aimentioning

confidence: 99%

An insight into the current perceptions of UK radiographers on the future impact of AI on the profession: A cross-sectional survey

Rainey¹,

O’Regan²,

Matthew³

et al. 2022

Journal of Medical Imaging and Radiation Sciences

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“…We have sought a range of perspectives, including experts from other professions, to start addressing some of these questions. [10][11][12] Data that takes the temperature of radiographers current attitudes towards AI is also included. 13,14 The need for radiographers to be both engaged in and leading research is increasingly important to support service developments and to assess the effectiveness of new technologies in imaging and therapeutic practice.…”

Section: Editorialmentioning

confidence: 99%