Using ChatGPT to Predict the Future of Diabetes Technology
Open accessThe 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.
Integrity signals
Registry
Cites
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.
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?
The most recent literature highlights the role of ChatGPT in basic and clinical medical sciences and its use in diabetes technology.
“The most recent literature highlights the role of ChatGPT in basic and clinical medical sciences, 9 and its use in diabetes technology.10”
From The Scientific Knowledge of Bard and ChatGPT in Endocrinology, Diabetes, and Diabetes Technology: Multiple-Choice Questions Examination-Based Performance (2025) · cites this paper as [10]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cited by
Sorted by citations
ChatGPT: Is this version good for healthcare and research?
Vaishya, R., Misra, A., & Vaish, A. (2023) · Diabetes & Metabolic Syndrome: Clinical Research & Reviews · doi:10.1016/j.dsx.2023.102744 · Cited by 293 · see citing works
Meo, S. A., Al-Khlaiwi, T., AbuKhalaf, A. A., Meo, A. S., & Klonoff, D. C. (2025) · Journal of Diabetes Science and Technology · doi:10.1177/19322968231203987 · Cited by 40 · see citing works
Self-citationCombining human and <scp>AI</scp> could predict nephrologies future, but should be handled with care
Alhasan, K., Raina, R., Jamal, A., & Temsah, M. (2023) · Acta Paediatrica · doi:10.1111/apa.16867 · Cited by 11 · see citing works
- Authors
- Huang, J., Yeung, A. M., Kerr, D., & Klonoff, D. C.
- Affiliations
- Diabetes Technology Society (US)
- San Mateo Medical Center (US)
- Corresponding author
- Klonoff, David C.
- Venue
- Journal of Diabetes Science and Technology
- Publisher
- SAGE Publications
- Published
- 2023-02-17
- Volume
- 17
- Issue
- 3
- Pages
- 853-854
- ISSN
- 1932-2968 (ISSN-L)
- PMC
- PMC10210126
- OpenAlex
- W4321165621
- Cited by
- 22
- References
- 0
- Citations by year
- 2025: 3 · 2024: 6 · 2023: 13
- FWCI
- 0.82
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Diabetes Science and Technology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- ChatGPT, large language models, diabetes technology, artificial intelligence in healthcare
- MeSH terms
- Artificial Intelligence, Diabetes Mellitus, Humans
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
