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      Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

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          Abstract

          Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

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          Most cited references27

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          High-performance medicine: the convergence of human and artificial intelligence

          Eric Topol (2019)
          The use of artificial intelligence, and the deep-learning subtype in particular, has been enabled by the use of labeled big data, along with markedly enhanced computing power and cloud storage, across all sectors. In medicine, this is beginning to have an impact at three levels: for clinicians, predominantly via rapid, accurate image interpretation; for health systems, by improving workflow and the potential for reducing medical errors; and for patients, by enabling them to process their own data to promote health. The current limitations, including bias, privacy and security, and lack of transparency, along with the future directions of these applications will be discussed in this article. Over time, marked improvements in accuracy, productivity, and workflow will likely be actualized, but whether that will be used to improve the patient-doctor relationship or facilitate its erosion remains to be seen.
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            International evaluation of an AI system for breast cancer screening

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              The potential for artificial intelligence in healthcare

              The complexity and rise of data in healthcare means that artificial intelligence (AI) will increasingly be applied within the field. Several types of AI are already being employed by payers and providers of care, and life sciences companies. The key categories of applications involve diagnosis and treatment recommendations, patient engagement and adherence, and administrative activities. Although there are many instances in which AI can perform healthcare tasks as well or better than humans, implementation factors will prevent large-scale automation of healthcare professional jobs for a considerable period. Ethical issues in the application of AI to healthcare are also discussed.
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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Healthcare (Basel)
                Healthcare (Basel)
                healthcare
                Healthcare
                MDPI
                2227-9032
                01 July 2021
                July 2021
                : 9
                : 7
                : 834
                Affiliations
                [1 ]Department Radiological Sciences, King Khalid University, Abha 61421, Saudi Arabia; mosalqhtani@ 123456kku.edu.sa (M.S.A.); aomer@ 123456kku.edu.sa (A.M.); 437804506@ 123456kku.edu.sa (H.A.); 436803611@ 123456kku.edu.sa (N.A.); 437804448@ 123456kku.edu.sa (F.A.)
                [2 ]Department Radiological Sciences, Taif University, Taif 21944, Saudi Arabia; s.alamri@ 123456tu.edu.sa
                [3 ]Center for Artificial Intelligence (CAI), King Khalid University, Abha 61421, Saudi Arabia; s.alelyani@ 123456kku.edu.sa
                [4 ]College of Computer Science, King Khalid University, Abha 61421, Saudi Arabia
                Author notes
                [* ]Correspondence: maalalyani@ 123456kku.edu.sa
                Author information
                https://orcid.org/0000-0002-6597-5090
                https://orcid.org/0000-0001-8876-1987
                https://orcid.org/0000-0002-6868-0298
                https://orcid.org/0000-0002-4571-9073
                Article
                healthcare-09-00834
                10.3390/healthcare9070834
                8307220
                34356212
                21304c8a-7428-49bd-823e-f737480c52d3
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 07 April 2021
                : 26 June 2021
                Categories
                Article

                ai,radiology,awareness,radiographers,radiologists
                ai, radiology, awareness, radiographers, radiologists

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