Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Aug 23:13:927-937.
doi: 10.2147/AMEP.S368519. eCollection 2022.

Undergraduate Medical Students' and Interns' Knowledge and Perception of Artificial Intelligence in Medicine

Nisha Jha  1 , Pathiyil Ravi Shankar  2 , Mohammed Azmi Al-Betar  3 , Rupesh Mukhia  4 , Kabita Hada  5 , Subish Palaian  6   7
Affiliations

Undergraduate Medical Students' and Interns' Knowledge and Perception of Artificial Intelligence in Medicine

Nisha Jha et al. Adv Med Educ Pract. .

Abstract

Purpose: Artificial intelligence (AI) is playing an increasingly important role in healthcare and health professions education. This study explored medical students' and interns' knowledge of artificial intelligence (AI), perceptions of the role of AI in medicine, and preferences around the teaching of AI competencies.

Methods: In this cross-sectional study, the authors used a previously validated Canadian questionnaire and gathered responses from students and interns at KIST Medical College, Nepal. Face validity and reliability of the tool were assessed by administering the questionnaire to 20 alumni as a pilot sample (Cronbach alpha = 0.6). Survey results were analyzed quantitatively (p-value = 0.05).

Results: In total 216 students (37% response rate) participated. The median AI knowledge score was 11 (interquartile range 4), and the maximum possible score was 25. The score was higher among final year students (p = 0.006) and among those with additional training in AI (p = 0.040). Over 49% strongly agreed or agreed that AI will reduce the number of jobs for doctors. Many expect AI to impact their specialty choice, felt the Nepalese health-care system is ill-equipped to deal with the challenges of AI, and opined every student of medicine should receive training on AI competencies.

Conclusion: The lack of coverage of AI and machine learning in Nepalese medical schools has resulted in students being unaware of AI's impact on individual patients and the healthcare system. A high perceived willingness among respondents to learn about AI is a positive sign and a strong indicator of futuristic successful curricula changes. Systematic implementation of AI in the Nepalese healthcare system can be a potential tool in addressing health-care challenges related to resource and manpower constraints. Incorporating topics related to AI and machine learning in medical curricula can be a useful first step.

Keywords: Nepal; artificial intelligence; healthcare; machine learning; medical students.

PubMed Disclaimer

Conflict of interest statement

The authors report no conflicts of interest in this work.

References

    1. Webster CS. Artificial intelligence and the adoption of new technology in medical education. Med Educ. 2021;55(1):6–7. doi: 10.1111/medu.14409 - DOI - PubMed
    1. Obermeyer Z, Emanuel EJ. Predicting the future - big data, machine learning, and clinical. Medicine N Engl J Med. 2016;375(13):1216–1219. doi: 10.1056/NEJMp1606181 - DOI - PMC - PubMed
    1. Lee J, Wu AS, Li D, Kulasegaram KM. Artificial intelligence in undergraduate medical education: a scoping review. Acad Med. 2021;96(11S):S62–S70. doi: 10.1097/ACM.0000000000004291 - DOI - PubMed
    1. Rajkomar A, Dean J, Kohane I. Machine learning in medicine. N Engl J Med. 2019;380(14):1347–1358. doi: 10.1056/NEJMra1814259 - DOI - PubMed
    1. Erickson BJ, Korfiatis P, Akkus Z, Kline TL. Machine learning for medical imaging. Radiographics. 2017;37(2):505–515. doi: 10.1148/rg.2017160130 - DOI - PMC - PubMed

LinkOut - more resources