Towards bridging the gap between pre-medicine student artificial intelligence technologies capabilities and their future medical practices.
Keywords:
artificial intelligence, pre-medicine undergraduate students, career-readinessAbstract
SUBTHEME: Modes of learningPROBLEM
In recent years, the healthcare industry has witnessed a rapid integration of artificial intelligence technologies (AI-Ts) as they provide a wide variety of benefits (Baddal, Taner & Ozsahin, 2024). “Future physicians will need a broad range of skills to adequately use AI in clinical practice” (Paranjape, Schinkel, Nannan Panday, Car & Nanayakkara, 2019, pe16048). Thus, it is imperative we develop an understanding of key stakeholder capabilities to ensure effective training of future medical practitioners in the AI-Ts space. Currently whilst there is willingness there is lack of sufficient understanding or supportive education (AlZaabi, AlMaskari & AalAbdulsalam, 2023).
PLAN
We planned to benchmark the perceptions, understanding and expectations of rural medical pathway stakeholders (pre-medicine undergraduate students, academics, medical practitioners in university-affiliated rural hospitals) regarding AI-Ts in current and future medical practice. Knowledges gained would allow for modification of medical training, provision of targeted professional development for academic staff and mechanisms for better AI-T solutions in rural medical practice in the future.
ACTION
Initial work from a collaborative research project has identified these different stakeholder knowledges and has prototyped educational opportunities to better support pre-medicine undergraduate capabilities to support and develop AI-T solutions for rural health care in their future career pathway.
REFLECTION
There remains much work to do in this space but the rapid changes to AI-Ts will change how our future medical practice. There is an urgent need to ensure that appropriate training, collaboration and distributed leadership capabilities are developed in our future medical practitioners.
REFERENCES
AlZaabi, A., AlMaskari, S., & AalAbdulsalam A. (2023) Are physicians and medical students ready for artificial intelligence applications in healthcare? Digit Health, 9:20552076231152167. https://doi.org/10.1177/20552076231152167.
Baddal, B., Taner, F., & Ozsahin, D. U. (2024). Harnessing of artificial intelligence for the diagnosis and prevention of hospital-acquired infections: A systematic review. Diagnostics, 14(5), 484. https://doi.org/10.3390/diagnostics14050484.
Paranjape, K., Schinkel, M., Nannan Panday, R., Car, J., & Nanayakkara, P. (2019). Introducing artificial intelligence training in medical education. Journal of Medical Internet Research Medical Education, 5(2): e16048. https://doi.org/10.2196/16048.
Proceedings of the Australian Conference on Science and Mathematics Education, The University of Canberra, 18 – 19 September 2024, page X, ISSN Number TBA.