The perceptions of medical physicists towards relevance and impact of artificial intelligence

Santos, Josilene C. and Wong, Jeannie Hsiu Ding and Pallath, Vinod and Ng, Kwan Hoong (2021) The perceptions of medical physicists towards relevance and impact of artificial intelligence. Physical and Engineering Sciences in Medicine, 44 (3). pp. 833-841. ISSN 2662-4729, DOI

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Artificial intelligence (AI) is an innovative tool with the potential to impact medical physicists' clinical practices, research, and the profession. The relevance of AI and its impact on the clinical practice and routine of professionals in medical physics were evaluated by medical physicists and researchers in this field. An online survey questionnaire was designed for distribution to professionals and students in medical physics around the world. In addition to demographics questions, we surveyed opinions on the role of AI in medical physicists' practices, the possibility of AI threatening/disrupting the medical physicists' practices and career, the need for medical physicists to acquire knowledge on AI, and the need for teaching AI in postgraduate medical physics programmes. The level of knowledge of medical physicists on AI was also consulted. A total of 1019 respondents from 94 countries participated. More than 85% of the respondents agreed that AI would play an essential role in medical physicists' practices. AI should be taught in the postgraduate medical physics programmes, and that more applications such as quality control (QC), treatment planning would be performed by AI. Half of the respondents thought AI would not threaten/disrupt the medical physicists' practices. AI knowledge was mainly acquired through self-taught and work-related activities. Nonetheless, many (40%) reported that they have no skill in AI. The general perception of medical physicists was that AI is here to stay, influencing our practices. Medical physicists should be prepared with education and training for this new reality.

Item Type: Article
Uncontrolled Keywords: Artificial intelligence; Perception; Medical physics; Educational training; Clinical practice
Subjects: R Medicine > R Medicine (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Medicine
Faculty of Medicine > Biomedical Imaging Department
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 16 Apr 2022 04:52
Last Modified: 16 Apr 2022 04:52

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