Artificial intelligence chatbots will revolutionize how cancer patients access information: ChatGPT represents a paradigm-shift
Open accessAbstract
On November 30, 2022, OpenAI enabled public access to ChatGPT, a next-generation artificial intelligence with a highly sophisticated ability to write, solve coding issues, and answer questions. This communication draws attention to the prospect that ChatGPT and its successors will become important virtual assistants to patients and health-care providers. In our assessments, ranging from answering basic fact-based questions to responding to complex clinical questions, ChatGPT demonstrated a remarkable ability to formulate interpretable responses, which appeared to minimize the likelihood of alarm compared with Google’s feature snippet. Arguably, the ChatGPT use case presents an urgent need for regulators and health-care professionals to be involved in developing standards for minimum quality and to raise patient awareness of current limitations of emerging artificial intelligence assistants. This commentary aims to raise awareness at the tipping point of a paradigm shift.
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ChatGPT exhibited an impressive ability to formulate interpretable responses that were easily understood when compared with Google's feature snippet.
“Similarly, ChatGPT exhibited an impressive ability to formulate interpretable responses that were easily understood when compared with Google's feature snippet [34].”
From A systematic literature review of empirical research on ChatGPT in education (2024) · cites this paper as [34]
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Klotz, R., Pausch, T. M., Kaiser, J., Joos, M. C., Hecktor, R., Ahmed, A., Dörr-Harim, C., Mehrabi, A., Loos, M., Roth, S., et al. (2025) · HPB · doi:10.1016/j.hpb.2024.11.012 · Cited by 18 · see citing works
ChatGPT and medicine: how AI language models are shaping the future and health related careers
Yan, M., Cerri, G. G., & de Moraes, F. Y. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-02011-3 · Cited by 17 · see citing works
The Future of AI in Ovarian Cancer Research: The Large Language Models Perspective
Laios, A., Theophilou, G., Jong, D. D., & Kalampokis, E. (2023) · Cancer Control · doi:10.1177/10732748231197915 · Cited by 17 · see citing works
Chu, B., Modi, N. D., Menz, B. D., Bacchi, S., Kichenadasse, G., Paterson, C. C., Kovoor, J. G., Ramsey, I., Logan, J. M., Wiese, M. D., et al. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1584348 · Cited by 16 · see citing works
Self-citation
- Authors
- Hopkins, A. M., Logan, J. M., Kichenadasse, G., & Sorich, M. J.
- Affiliations
- Flinders University (AU)
- University of South Australia (AU)
- Corresponding author
- Hopkins, Ashley M
- Venue
- JNCI Cancer Spectrum
- Publisher
- Oxford University Press (OUP)
- Published
- 2023-02-21
- Volume
- 7
- Issue
- 2
- ISSN
- 2515-5091 (ISSN-L)
- PMC
- PMC10013638
- OpenAlex
- W4321436564
- Cited by
- 259
- References
- 3
- Citations by year
- 2026: 19 · 2025: 58 · 2024: 100 · 2023: 81 · 2022: 1
- FWCI
- 10.30
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- JNCI Cancer Spectrum (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- UniSA Research Outputs Repository (University of South Australia) (submittedVersion, other-oa)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by-nc)
- Funders
- National Health and Medical Research Council (APP2008119)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- ChatGPT, large language models, AI chatbots, cancer patients, patient data access, virtual assistants, medical question answering, AI regulation
- MeSH terms
- Artificial Intelligence, Communication, Health Personnel, Humans, Neoplasms, Probability
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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.
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