Influence of Artificial Intelligence on Canadian Medical Students' Preference for Radiology Specialty: ANational Survey Study

Artificial intelligence in radiology: who’s afraid of the big bad wolf?

“…Although the authors did not directly ask medical students in their survey if they would be less likely to choose a career in radiology because of AI, the above question indirectly suggest this. This is confirmed by another recent publication by Gong et al [7] that performed a similar survey in all 17 Canadian Medical Schools. This survey was more directly focused on the future of radiology in the eyes of medical students.…”

“…The reality is that AI technology will transform the radiology profession in a way that deserves to be better understood and taught at medical school. As demonstrated in the Canadian survey, medical students are not so much afraid of the replacement of radiologists, but rather of a Bdisplacement' with many tasks that could be replaced by machines and lead to a potential reduction of demand for radiologists [7]. Because these algorithms are by their nature standardized, repeatable, and scalable, they could be deployed to analyze a large number of images in hospitals around the world once an algorithm has been developed and validated, enabling radiologists to focus on other aspects of their practice.…”

Attitudes toward artificial intelligence in radiology with learner needs assessment within radiology residency programmes: a national multi-programme survey

“…(22) Question 7 listed the broad domains of AI/ML applications in radiology beyond automated feature detection as described by Choy et al (2) The third section probed subjective perception of AI/ML relating to career prospects, similar in focus to prior survey studies. (9,10) The fourth section examined education needs and expectations. Questions 17 and 18 within this section compared the importance of AI/ML training versus imaging physics, and versus clinical skills and knowledge, respectively, which paralleled the focuses of the First (Part 1) and Final (Parts 2A and 2B) FRCR examinations.…”

“…(4)(5)(6)(7)(8) In this capricious epoch, many educators have attempted to explore the perceptions of students toward AI in radiology in anticipation of the next phase of radiology training. (9)(10)(11)(12) These are also nascent efforts to emphasise an informatics curriculum within residency programmes and the development of AI/ML interest groups within professional bodies to aid continuing education. (13,14) Radiology residency in Singapore is a five-year programme modelled after American residency programmes and has been accredited by the American Accreditation Council for Graduate Medical Education International (ACGME-I) since year 2011.…”

Priorities, factors and alternatives involved in the choice of medical specialty – an empirical study on year sixth medical students

“…The most commonly addressed personal characteristics include demographics [9][10][11][12][13][14], personality [9,[15][16][17], skills, values, aspirations [12,[18][19][20][21], academic and career opportunities [22] and expectations of family members [23][24][25][26]. As far as the training process itself is concerned, technological challenges, examples of physicians with the background, the possibility to obtain a residency position, the length of residency required, working hours and lifestyle during training all influence the decision to commence training [22,[27][28][29][30][31][32] as well as work-related hazards, such as infections from AIDS or hepatitis patients [33][34][35] and independent work [12,32]. When selecting a specialty medical students may also consider the various features of future work which may follow from it.…”