Insights from teaching artificial intelligence to medical students in Canada

Hu, Ricky; Fan, Kevin; Pandey, Prashant; Hu, Zoe; Yau, Olivia; Teng, Minnie; Wang, Patrick; Li, Anthony; Ashraf, Mishal; Singla, Rohit

doi:10.1038/s43856-022-00125-4

Cited by 36 publications

(29 citation statements)

References 14 publications

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“…Therefore, medical/health professors and students should be mindful of how to incorporate this AI platform into medical/health education soon. Furthermore, AI should be integrated into the medical school curriculum, and some schools have already adopted it [6]. He was not involved in the review process.…”

Section: Generalizabilitymentioning

confidence: 99%

Are ChatGPT's knowledge and interpretation ability comparable to those of medical students in Korea for taking a parasitology examination?: a descriptive study

Huh

2023

J Educ Eval Health Prof

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This study aimed to compare the knowledge and interpretation ability of ChatGPT, a language model of artificial general intelligence, with those of medical students in Korea by administering a parasitology examination to both ChatGPT and medical students. The examination consisted of 79 items and was administered to ChatGPT on January 1, 2023. The examination results were analyzed in terms of ChatGPT's overall performance score, its correct answer rate by the items’ knowledge level, and the acceptability of its explanations of the items. ChatGPT's performance was lower than that of the medical students, and ChatGPT's correct answer rate was not related to the items’ knowledge level. However, there was a relationship between acceptable explanations and correct answers. In conclusion, ChatGPT's knowledge and interpretation ability for this parasitology examination were not yet comparable to those of medical students in Korea.

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Section: Generalizabilitymentioning

confidence: 99%

Are ChatGPT's knowledge and interpretation ability comparable to those of medical students in Korea for taking a parasitology examination?: a descriptive study

Huh

2023

J Educ Eval Health Prof

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“…The American Medical Association encourages 'medical specialty societies and boards to consider production of specialty-specific educational modules related to artificial intelligence' [1]. Several initiatives, such as medical student elective courses and physician CME courses by professional societies, incorporate artificial intelligence in medical education [53,54]. Artificial intelligence and data sciences are currently not included within common program requirements or requirements for resident/ fellow scholarly activity by ACGME [55,56].…”

Section: Proposal For Artificial Intelligence Curriculum For Neurolog...mentioning

confidence: 99%

Neurology education in the era of artificial intelligence

Kedar¹,

Khazanchi

2022

Current Opinion in Neurology

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Purpose of reviewThe practice of neurology is undergoing a paradigm shift because of advances in the field of data science, artificial intelligence, and machine learning. To ensure a smooth transition, physicians must have the knowledge and competence to apply these technologies in clinical practice. In this review, we describe physician perception and preparedness, as well as current state for clinical applications of artificial intelligence and machine learning in neurology. Recent findingsDigital health including artificial intelligence-based/machine learning-based technology has made significant inroads into various aspects of healthcare including neurological care. Surveys of physicians and healthcare stakeholders suggests an overall positive perception about the benefits of artificial intelligence/machine learning in clinical practice. This positive perception is tempered by concerns for lack of knowledge and limited opportunities to build competence in artificial intelligence/machine learning technology. Literature about neurologist's perception and preparedness towards artificial intelligence/ machine learning-based technology is scant. There are very few opportunities for physicians particularly neurologists to learn about artificial intelligence/machine learning-based technology. SummaryNeurologists have not been surveyed about their perception and preparedness to adopt artificial intelligence/machine learning-based technology in clinical practice. We propose development of a practical artificial intelligence/machine learning curriculum to enhance neurologists competence in these newer technologies.

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“…As the champions of technological change in medicine, radiologists must educate themselves, translate their knowledge to their trainees and translate the role of AI to patients, as some may not trust AI to be involved in decision-making towards their care. 4,5 Another misconception that medical students and radiologists may have towards working with AI is that they will need to learn new skills, such as coding, in order to use AI as a radiologist. This is not true.…”

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confidence: 99%

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confidence: 99%

“…The best way build this foundation of AI knowledge is to invest in high-quality, clinically-focused AI education for both undergraduate and graduate medical education programmes. 4 This requires early introduction of these topics, ideally in the first year of medical school, to dispel misconceptions and provide students with enough experiential learning time to become familiar with using AI. There are currently no standardized guidelines, objectives or competencies outlined by the Medical Council of Canada or the Royal College of Physicians and Surgeons of Canada for teaching AI to undergraduate or postgraduate medical learners, despite the movement to more competency-based training.…”

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confidence: 99%

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