Stakeholders’ perspectives on the future of artificial intelligence in radiology: a scoping review

Ling, Yang; Ene, Ioana Cezara; Belaghi, Reza Arabi; Koff, David; Stein, Nina Rodrigues; Santaguida, Pasqualina

doi:10.1007/s00330-021-08214-z

Cited by 74 publications

(43 citation statements)

References 80 publications

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“…Surveys showed that more than 50% of radiologists have limited knowledge of AI [52,53]. Similar findings were also reported in Yang et al in which their survey showed that most stakeholders expressed education on AI is needed to enhance collaborative work in AI implementation [54]. Furthermore, some studies reported that healthcare workers are hesitant to accept new technologies due to the fear of altering their routine that may lead to increased workload [55][56][57][58].…”

Section: Stakeholder Consensussupporting

confidence: 70%

Current challenges of implementing artificial intelligence in medical imaging

Saw

2022

Physica Medica

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Section: Stakeholder Consensussupporting

confidence: 70%

Current challenges of implementing artificial intelligence in medical imaging

Saw

2022

Physica Medica

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“…In line with the first objective of the study, we analysed the main challenges in the design and integration of Artificial Intelligence in digital radiology. The eligibility process led to the choice of 20 papers [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ], among which there are mainly reviews (15 in number) (as it could be expected considering the broad topics covered) but also 5 recent scientific articles/focus articles on very specific aspects [ 15 , 26 , 27 , 29 , 30 ].…”

Section: Resultsmentioning

confidence: 99%

“…According to the authors, these skills would then have to be transferred, explained, and taught to the data science experts to facilitate their comprehension and integration algorithms. The study by Pesapane et al [ 21 ] reported how the role of the stakeholders was also considered strategic in this team game. The authors reported that the stakeholders had the opinion that Artificial Intelligence could improve the practice of radiology and that they considered the replacement of radiologists unlikely.…”

Section: Resultsmentioning

confidence: 99%

“…The third topic related to the new spreading IT tools that could be strategic in the health domain [ 17 , 18 , 19 ]. This determined (and hence the fourth topic) the need to intensify the collaboration between [ 19 , 20 , 21 ] the insiders. The fifth topic is the need of targeted training also including the mobility in the territory [ 22 , 30 ].…”

Section: Discussionmentioning

confidence: 99%

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The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus

Giansanti

Basilio

2022

Healthcare

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Artificial intelligence is having important developments in the world of digital radiology also thanks to the boost given to the research sector by the COVID-19 pandemic. In the last two years, there was an important development of studies focused on both challenges and acceptance and consensus in the field of Artificial Intelligence. The challenges and acceptance and consensus are two strategic aspects in the development and integration of technologies in the health domain. The study conducted two narrative reviews by means of two parallel points of view to take stock both on the ongoing challenges and on initiatives conducted to face the acceptance and consensus in this area. The methodology of the review was based on: (I) search of PubMed and Scopus and (II) an eligibility assessment, using parameters with 5 levels of score. The results have: (a) highlighted and categorized the important challenges in place. (b) Illustrated the different types of studies conducted through original questionnaires. The study suggests for future research based on questionnaires a better calibration and inclusion of the challenges in place together with validation and administration paths at an international level.

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“…However, even though many survey participants stated to believe that AI applications will become increasingly important within the next 10 years, they mentioned to experience substantial deficits in the implementation of AI applications in their own professional environment. Physicians from other specialties share these concerns: In the field of radiology, Yang et al have reported that students and physicians believe that AI-literacy training during medical school and residency is inadequate ( 29 ). Accordingly, the respondents emphasized the need for education and training in AI ( 29 ).…”

Section: Discussionmentioning

confidence: 99%

The use and future perspective of Artificial Intelligence—A survey among German surgeons

Pecqueux

Riediger

Distler

et al. 2022

Front. Public Health

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PurposeClinical abundance of artificial intelligence has increased significantly in the last decade. This survey aims to provide an overview of the current state of knowledge and acceptance of AI applications among surgeons in Germany.MethodsA total of 357 surgeons from German university hospitals, academic teaching hospitals and private practices were contacted by e-mail and asked to participate in the anonymous survey.ResultsA total of 147 physicians completed the survey. The majority of respondents (n = 85, 52.8%) stated that they were familiar with AI applications in medicine. Personal knowledge was self-rated as average (n = 67, 41.6%) or rudimentary (n = 60, 37.3%) by the majority of participants. On the basis of various application scenarios, it became apparent that the respondents have different demands on AI applications in the area of “diagnosis confirmation” as compared to the area of “therapy decision.” For the latter category, the requirements in terms of the error level are significantly higher and more respondents view their application in medical practice rather critically. Accordingly, most of the participants hope that AI systems will primarily improve diagnosis confirmation, while they see their ethical and legal problems with regard to liability as the main obstacle to extensive clinical application.ConclusionGerman surgeons are in principle positively disposed toward AI applications. However, many surgeons see a deficit in their own knowledge and in the implementation of AI applications in their own professional environment. Accordingly, medical education programs targeting both medical students and healthcare professionals should convey basic knowledge about the development and clinical implementation process of AI applications in different medical fields, including surgery.

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Stakeholders’ perspectives on the future of artificial intelligence in radiology: a scoping review

Cited by 74 publications

References 80 publications

Current challenges of implementing artificial intelligence in medical imaging

Current challenges of implementing artificial intelligence in medical imaging

The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus

The use and future perspective of Artificial Intelligence—A survey among German surgeons

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