Machine learning in medical education: a survey of the experiences and opinions of medical students in Ireland

Charlotte Blease, Anna Kharko, Michael Bernstein, Colin Bradley, Muiris Houston, Ian Walsh, Maria Hägglund, Catherine DesRoches, Kenneth D Mandl

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Abstract

Leading figures in biomedical informatics advocate education in digital health for the healthcare workforce.1 2 In healthcare, artificial intelligence/machine learning (AI/ML)-enabled tools increasingly play a role by informing patient triage decisions, clinical decision support systems, and healthcare resource management3 – advances that are undoubtedly set to grow.4 Tens of thousands of healthcare apps are available for download by consumers, promising a range of services, from symptom tracking to diagnostic and treatment advice.

To date, surveys of medical professionals reveal divergent views about the value and impact of AI/ML on their job with many physicians sceptical about the potential scope for technological innovations on medical tasks.5–7 Furthermore, surveys consistently find limited evidence of formal teaching in medical education about AI/ML. Only a few studies – conducted in Europe, the US and South Korea – have explored the formal education and familiarity of medical or healthcare students with respect to digital advances in healthcare, and much of this work consists of single site studies.8–14 To better understand and engage with discussion about the benefits, limitations, and ethical dilemmas presented by these tools, today’s medical students will need to become more digitally savvy. Equally, as patients make increasing use of healthcare and well-being algorithms, medical students will need to become better prepared to offer patients advice, and to have knowledge about, the robustness of these tools including when algorithms are safe to use.

In the present study, we built on this research by assessing the experiences and opinions of final year medical students throughout Ireland about their exposure to AI/ML during their entire degree programme.
Original languageEnglish
Article numbere100480
JournalBMJ health & care informatics
Volume29
Issue number1
DOIs
Publication statusPublished - 01 Feb 2022

Keywords

  • machine learning
  • artificial intelligence

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