“Artificial intelligence” (AI) is a broad term that refers to technology that enables robots and computers to mimic human intellect . While the information age is giving way to the era of artificial intelligence, certain professions, notably medicine, will be disproportionately impacted by this environment. AI technology is advancing at a breakneck pace and is transforming the realm of medicine, most notably via a process sparked by the Covid-19 epidemic. AI technologies are developed to analyze a variety of health data, including clinical, behavioral, environmental, and drug information, and data from biomedical literature as well as patients . Apart from several other advancements, diagnosis and therapy can now be performed more quickly and precisely, imaging methods are improving, doctors and patients may be assisted by guiding surgery, drug research is facilitated, and more personalized therapies are feasible [2, 3]. Modern medicine, in general, takes a futuristic view of these identified difficulties. This futuristic tendency increases the appeal of AI applications in medicine, which look to be becoming more integrated into healthcare. The futurist author Eric Topol’s words “Nearly every clinician in the future; from specialist physicians to paramedics, will be using artificial intelligence technology and especially deep learning.” underlined the wide field of use of AI in medicine . On the other hand, there are numerous ethical concerns, including the threat to data security, the changing nature of the patient-physician relationship in health, the generation of potential social inequalities, and the development of AI robots that may eventually replace many professional tasks, resulting in increasing unemployment rates.
Healthcare providers are responsible for ensuring that AI applications provide useful technology in support of patient care. For this reason, gaining adequate knowledge and skills regarding AI applications in medicine is crucial for medical students, who may even have to use applications that did not exist during their education. Thus, the World Medical Association advocates for a review of medical curricula and educational opportunities for patients, physicians, medical students, health administrators, and other health care professionals to foster a better understanding of the numerous aspects of health care AI, both positive and negative . Additionally, in a 2019 statement, the Standing Committee of European Doctors (CPME) stressed the need to use AI systems in basic and continuing medical education . They proposed that AI systems be integrated into medical education, residency training, and continuing medical education courses to increase awareness of the proper use of AI. However, many authors in the literature stress that today’s medical education cannot meet the needs of AI and that a fundamental and compulsory change in education should be undertaken [2, 6–11]. Developing curriculum proposals specifically designed to train future physicians on AI would be a valuable contribution in that regard.
Understanding how today’s medical student perceives AI in medicine, what they know and don’t know, and their comprehension of AI’s ethical dimensions, is a crucial first step to developing effective AI curricula. Kern et al define one of the steps of curriculum development as “Needs Assessment of Targeted Learners”, a process by which curriculum developers identify the differences between the ideal and the actual characteristics of the targeted learner group . Likewise, The CanMEDS Physician Competency Framework, a globally recognized framework that identifies the abilities physicians require to effectively serve, defines the needs assessment as identifying perceived and unperceived needs . Grunhut et al recommends that national surveys of medical students on the attitudes and expectations of learning AI in medical school should be carried out for developing curricula, and these surveys should identify the realistic goals physicians will be asked to meet, the expectations that will be put upon future physicians, and the resources and knowledge faculty members will need to meet these expectations . Current studies in the literature fall short of a comprehensive needs assessment; they are limited in number and mainly focused on students’ knowledge and opinions on AI in medicine. The limited foci of the relevant studies can be categorized as follows;
‘Familiarity with AI’ (Pinto dos Santos et al (263 students / 3 medical schools in Germany) , Bisdas et al (3,133 students / 63 countries) , Wood et al (121 students – 1 medical school in the USA) , Oh et al (121 students − 1 medical school in Rebuplic of Korea) , Blease et al (252 students – 4 medical schools in Ireland) , Mehta et al (321 students – 4 medical schools in Canada) , Sit et al (484 students – 19 medical schools in the UK) ),
‘General thoughts of students on AI in medicine’ ([7, 16–18], Cho et al (100 students / 1 medical school in Rebuplic of Korea) ),
‘Concerns about replacing physicians and losing jobs’ [15, 16, 18, 20–22],
‘Possible risks of AI in medicine’ ,
‘Thoughts on the inclusion of AI in medical curriculum’ [15, 17, 19–22].
In general, the findings conclude that future physicians are usually not familiar with AI, their concern of losing their jobs is considerable, they are enthusiastic to learn and use AI in their practice, and they think AI applications in medicine should be integrated into the curriculum. In addition to those subjects, trainee’s thoughts on the possible influences of AI on medicine and the topics they wish to see integrated into the medical curriculum would be a significant contribution to what is already known, one that advances a more complete needs assessment of targeted learners. Bisdas et al concluded that there might be a high demand to have AI topics integrated into the university curricula which should be further explored . To the best of our knowledge, Wood et al’s study with 117 medical students on seven topics is the only one in the literature that investigated the importance of AI topics in the eyes of the students. Hence, in this study, we aimed to examine medical students’ perceptions regarding the possible influence of AI on medicine and also their thoughts on the AI topics to be integrated into the medical curriculum.