The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
The exciting potential for ChatGPT in obstetrics and gynecology
Open accessAbstract
Natural language processing-the branch of artificial intelligence concerned with the interaction between computers and human language-has advanced markedly in recent years with the introduction of sophisticated deep-learning models. Improved performance in natural language processing tasks, such as text and speech processing, have fueled impressive demonstrations of these models' capabilities. Perhaps no demonstration has been more impactful to date than the introduction of the publicly available online chatbot ChatGPT in November 2022 by OpenAI, which is based on a natural language processing model known as a Generative Pretrained Transformer. Through a series of questions posed by the authors about obstetrics and gynecology to ChatGPT as prompts, we evaluated the model's ability to handle clinical-related queries. Its answers demonstrated that in its current form, ChatGPT can be valuable for users who want preliminary information about virtually any topic in the field. Because its educational role is still being defined, we must recognize its limitations. Although answers were generally eloquent, informed, and lacked a significant degree of mistakes or misinformation, we also observed evidence of its weaknesses. A significant drawback is that the data on which the model has been trained are apparently not readily updated. The specific model that was assessed here, seems to not reliably (if at all) source data from after 2021. Users of ChatGPT who expect data to be more up to date need to be aware of this drawback. An inability to cite sources or to truly understand what the user is asking suggests that it has the capability to mislead. Responsible use of models like ChatGPT will be important for ensuring that they work to help but not harm users seeking information on obstetrics and gynecology.
Overview
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.
Integrity signals
Registry
Cites
Statistics
Verification
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?
In the citing paper
“Second, due to the nature of its training data [78], the information incorporated into ChatGPT may have delays and incompleteness [8,79].”
From Ethical Considerations of Using ChatGPT in Health Care (2023) · cites this paper as [79]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Writing Group for the Women's Health Initiative Investigators (2002) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.288.3.321 · Cited by 15,889
Artificial intelligence: A modern approach
Nilsson, N. J. (1996) · Artificial Intelligence · doi:10.1016/0004-3702(96)00007-0 · Cited by 10,730
Prevention of recurrent preterm delivery by 17 alpha–hydroxyprogesterone caproate
Meis, P. J., Klebanoff, M., Thom, E., Dombrowski, M. P., Sibai, B., Moawad, A. H., Spong, C. Y., Hauth, J. C., Miodovnik, M., Varner, M. W., et al. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa035140 · Cited by 1,555
ChatGPT and other large language models are double-edged swords
Shen, Y., Heacock, L., Elias, J., Hentel, K. D., Reig, B., Shih, G., & Moy, L. (2023) · Radiology · doi:10.1148/radiol.230163 · Cited by 1,008
Hassan, S. S., Romero, R., Vidyadhari, D., Fusey, S., Baxter, J. K., Khandelwal, M., Vijayaraghavan, J., Trivedi, Y., Soma‐Pillay, P., Sambarey, P., et al. (2011) · Ultrasound in Obstetrics & Gynecology · doi:10.1002/uog.9017 · Cited by 923
ChatGPT and the future of medical writing
Biswas, S. (2023) · Radiology · doi:10.1148/radiol.223312 · Cited by 571
Romero, R., Conde-Agudelo, A., Da Fonseca, E., O’Brien, J. M., Cetingoz, E., Creasy, G. W., Hassan, S. S., & Nicolaides, K. H. (2018) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2017.11.576 · Cited by 522
Sarraju, A., Bruemmer, D., Iterson, E. H. V., Cho, L., Rodríguez, F., & Laffin, L. J. (2023) · JAMA · doi:10.1001/jama.2023.1044 · Cited by 466
Prevention of preeclampsia with aspirin
Rolnik, D. L., Nicolaides, K. H., & Poon, L. C. (2020) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2020.08.045 · Cited by 445
Flanagin, A., Bibbins-Domingo, K., Berkwits, M., & Christiansen, S. L. (2023) · JAMA · doi:10.1001/jama.2023.1344 · Cited by 420
Research works printed but not linked: 3
- Richards EMF, Giorgione V, Stevens O, Thilaganathan B. Low-dose aspirin for the prevention of superimposed preeclampsia in women with chronic hypertension: a systematic review and meta-analysis. Am J Obstet Gynecol [In press].
- 2022, ACOG committee opinion, number 819, Obstet Gynecol, 137, e34
- Kitamura FC. ChatGPT is shaping the future of medical writing but still requires human judgment. Radiology [In press].
Cited by
Sorted by citations
Grassini, S. (2023) · Education Sciences · doi:10.3390/educsci13070692 · Cited by 1,048
Ethical Considerations of Using ChatGPT in Health Care
Wang, C., Liu, S., Yang, H., Guo, J., Wu, Y., & Liu, J. (2023) · Journal of Medical Internet Research · doi:10.2196/48009 · Cited by 541
Utility of ChatGPT in Clinical Practice
Liu, J., Wang, C., & Liu, S. (2023) · Journal of Medical Internet Research · doi:10.2196/48568 · Cited by 505
A study of generative large language model for medical research and healthcare
Peng, C., Yang, X., Chen, A., Smith, K. E., PourNejatian, N., Costa, A. B., Martin, C., Flores, M. G., Zhang, Y., Magoc, T., et al. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00958-w · Cited by 408
ChatGPT for healthcare services: An emerging stage for an innovative perspective
Javaid, M., Haleem, A., & Singh, R. P. (2023) · BenchCouncil Transactions on Benchmarks, Standards and Evaluations · doi:10.1016/j.tbench.2023.100105 · Cited by 429
Metadata
- Authors
- Grünebaum, A., Chervenak, J., Pollet, S. L., Katz, A., & Chervenak, F. A.
- Affiliations
- Albert Einstein College of Medicine (US)
- Lenox Hill Hospital (US)
- Venue
- American Journal of Obstetrics and Gynecology
- Publisher
- Elsevier BV
- Published
- 2023-06
- Volume
- 228
- Issue
- 6
- Pages
- 696-705
- ISSN
- 0002-9378 (ISSN-L)
- OpenAlex
- W4324370593
- Cited by
- 234
- References
- 58
- Citations by year
- 2026: 22 · 2025: 60 · 2024: 77 · 2023: 74
- FWCI
- 9.28
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- American Journal of Obstetrics and Gynecology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- ChatGPT, generative AI, natural language processing, obstetrics and gynecology, medical information retrieval, misinformation, responsible AI use, medical education
- MeSH terms
- Artificial Intelligence, Awareness, Educational Status, Female, Gynecology, Humans, Obstetrics, Pregnancy
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
