JMIR Publications

ABSTRACT

Background:

Artificial intelligence (AI) is set to shape the future of medical practice. The perspective and understanding of medical students are critical for guiding the development of educational curricula and training.

Objective:

To assess and compare medical AI-related attitudes among medical students in general medicine and in one of the visually oriented fields (Pathology), along with illuminating their anticipated role of AI in the rapidly evolving landscape of AI-enhanced healthcare.

Methods:

A cross-sectional study using a web-based survey composed of a closed-ended questionnaire. The survey addresses medical students at all educational levels across the five public medical schools, along with pathology residents in four residency programs in Jordan.

Results:

A total of 394 respondents participated (328 medical students and 66 pathology residents). The majority of respondents (69%, n = 272) were already aware of artificial intelligence and deep learning in medicine, mainly relying on websites for information on AI, while only 14% (n = 56) were aware of AI through medical schools. There was a statistically significant difference in awareness among respondents who consider themselves tech experts compared to those who do not (P =.03). Over half of respondents believed AI could be used to diagnose diseases automatically (54.1%, n = 213 agreement), with medical students agreeing more than pathology residents (P =.04). However, over one-third expressed fear about recent AI developments (42.4%, n = 167 agreed). Two-thirds of respondents disagreed that their medical schools had educated them about AI and its potential use, while 46.2% (n = 182) expressed interest in learning about AI in medicine. In terms of pathology-specific questions, 75.4% (n = 297) agreed that AI could be used to identify pathologies in slide exams automatically. There was a significant difference between medical students and pathology residents in their agreement (P =.001). Overall, medical students and pathology trainees had similar responses.

Conclusions:

AI education should be introduced into medical school curricula to improve medical students' understanding and attitudes. Students agreed that they need to learn about AI's applications, potential hazards, and legal and ethical implications. This is the first study to analyse medical students' views and awareness of artificial intelligence in Jordan, as well as the first to include pathology residents' perspectives. The findings are consistent with earlier research internationally. In comparison with prior research, these attitudes are similar in low-income and industrialised countries, highlighting the need for a global strategy to introduce AI instruction to medical students everywhere in this era of rapidly expanding technology.