Cited by 31Artificial Intelligence in Healthcare and EducationArtificial Intelligence in EducationInnovations in Medical Education

Incorporating AI tools into medical education: harnessing the benefits of ChatGPT and Dall-E

Open access
Miftahul Amri, Muhammad, Khairatun Hisan, Urfa·2023·Journal of Novel Engineering Science and Technology

Abstract

Artificial intelligence (AI) has shown promising potential to transform various fields, including medical education. Recently, the rapid advancement of AI has led to many ``new'' discoveries that caught everyone's attention. Among those discoveries are introduced by OpenAI (e.g., ChatGPT, Dall-E, and the most recent, GPT-4). The integration of AI tools, such as ChatGPT and Dall-E, can offer a new dimension to medical education by creating an interactive and engaging learning experience. In this article, we explore the potential benefits of ChatGPT and Dall-E in medical education and provide practical utilization examples of those tools. For starters, ChatGPT, or in this sense, any other similar large language models, can simulate patient interactions in a safe environment, allowing medical learners to practice their communication skills and diagnosis techniques. Furthermore, it can assist medical students and researchers in reading and writing academic articles by accurately summarizing the key points of a given topic and generating an indistinguishable abstract. In addition, ChatGPT can also create problems for medical assignments and exam practice. In this article, we also discussed ChatGPT's capability to answer standard medical assignment problems. Dall-E, on the other hand, can generate dummy copyright-free and consent-free medical images (e.g., x-ray and electrocardiogram (ECG) graphs), allowing medical learners to practice and enhance their interpretation skills. Incorporating AI-based tools into medical education can provide a new approach to teaching and learning, bridging the gap between theory and practice, and unlocking new avenues for learning and discoveries for both, the students and the instructors. It can also offer a cost-effective solution to simulate real-world scenarios that would otherwise require significant resources and time. In summary, this article concludes that AI-based tools have the potential to revolutionize medical education, empowering medical learners with the skills and knowledge necessary to excel in their field.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.56741/jnest.v2i02.315

Cites

19 of 19 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

2 retracted

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Miftahul Amri, M., & Khairatun Hisan, U.
Venue
Journal of Novel Engineering Science and Technology
Published
2023-04-24
Volume
2
Issue
02
Pages
34-39
ISSN
  • 2961-8738 (ISSN-L)
  • 2961-8916
OpenAlex
W4368365160
Cited by
31
References
19
Citations by year
2026: 4 · 2025: 13 · 2024: 10 · 2023: 4
FWCI
1.25
Type
journal article
Language
en
Open access
Locations
Journal of Novel Engineering Science and Technology (publishedVersion, cc-by-sa)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
Keywords
artificial intelligence in medical education, ChatGPT, DALL-E, large language models, simulated patient encounters, communication skills training, academic writing support, exam question generation, medical image synthesis, AI-generated images

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review