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ChatGPT-4: Transforming Medical Education and Addressing Clinical Exposure Challenges in the Post-pandemic Era

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Indian Journal of Orthopaedics Aims and scope Submit manuscript

Abstract

Background

The COVID-19 pandemic has affected medical education, constraining clinical exposure and posing unprecedented challenges for students and junior doctors. This research explores the potential of artificial intelligence (AI), specifically the ChatGPT-4 language model, to transform medical education and address the deficiencies in clinical exposure during the post-pandemic era.

Research Questions/Purpose

What is the potential of AI large language models in delivering safe and coherent medical advice to junior doctors for clinical orthopaedic scenarios?

Patients and Methods

A series of diverse orthopaedic questions was presented to ChatGPT-4, from general medicine to highly specialised fields. The questions were based on a variety of common orthopaedic presentations including neck of femur fracture, compartment syndrome, pulmonary embolism, and a motor vehicle accident. A validated questionnaire (Likert Scale) was implemented to evaluate the answers produced by ChatGPT-4.

Results

Our results indicate that ChatGPT-4 exhibits exceptional proficiency in delivering accurate and coherent medical advice. Its intuitive interface, accessibility, and sophisticated algorithm render it an ideal supplementary tool for medical students and junior doctors. Despite certain limitations, such as its inability to fully address highly specialised areas, this study highlights the potential of AI and ChatGPT-4 to revolutionise medical education and fill the clinical exposure void generated by the pandemic. Future research should concentrate on the practical application of ChatGPT-4 in real-world medical environments and its integration with other emerging technologies to optimise its influence on the education and training of healthcare professionals.

Conclusions

ChatGPT-4’s integration into orthopaedic education and practice can mitigate pandemic-related experience gaps, promoting self-directed, personalised learning and decision-making support for interns and residents. Future advancements may address limitations to enhance healthcare professionals' learning and expertise.

Level of Evidence

Level III evidence—observational study.

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Dta availability

Data for this study is freely available in the appendix/figures. No additional data was used.

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No funding was obtained for this research.

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Authors and Affiliations

  1. Department of Orthopaedics, St George Hospital, Gray Street, Sydney, NSW, 2000, Australia

    Kirk Lower

  2. Faculty of Science, Medicine, and Health, Central Clinical School at Monash University, The Alfred Centre, 99 Commercial Rd, Melbourne, VIC, 3004, Australia

    Ishith Seth & Bryan Lim

  3. Department of Orthopaedic Surgery, Peninsula Health, Melbourne, VIC, 3004, Australia

    Ishith Seth, Bryan Lim & Nimish Seth

Authors
  1. Kirk Lower
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  2. Ishith Seth
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  3. Bryan Lim
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  4. Nimish Seth
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Correspondence to Kirk Lower.

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The authors declare no conflict of interest.

Ethical Standard Statement

This article does not contain any studies with human or animal subjects performed by the any of the authors.

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Due to this study’s design, no institutional ethics was required.

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Lower, K., Seth, I., Lim, B. et al. ChatGPT-4: Transforming Medical Education and Addressing Clinical Exposure Challenges in the Post-pandemic Era. JOIO 57, 1527–1544 (2023). https://doi.org/10.1007/s43465-023-00967-7

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  • DOI: https://doi.org/10.1007/s43465-023-00967-7

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