Harvesting the Power of Artificial Intelligence for Surgery: Uses, Implications, and Ethical Considerations
Open accessAbstract
Artificial intelligence is rapidly advancing, especially with the advent of ChatGPT technology, and its role in the world of medicine is expanding. Within surgery, AI has the capacity to improve efficiency and results in surgical treatments; however, it similarly has the potential to impose harm onto patients and undermine the role of medical providers. Its benefits may include improvements in surgical outcomes, spanning from enhanced pre-operative diagnostic capabilities to more refined intra-operative techniques, and long term patient experiences, by identifying and reducing complications. Nevertheless apprehensions revolve around laymen use potentially resulting in inappropriate therapeutic interventions, in addition to safety and ethical risks surrounding the use of patient data. Various strategies towards mitigating these harms must be considered, such as patient disclaimers and secondary review policies. While artificial intelligence brings exciting advancements to surgery, its integration must be cautiously monitored.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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 integration of ChatGPT into medical practices and healthcare settings presents challenges and ethical considerations.
“The integration of ChatGPT into medical practices and healthcare settings presents challenges and ethical considerations.”
Ethical concerns arise when content generated by AI is mistaken for the expertise of a human.
“Ethical concerns arise when content generated by AI is mistaken for the expertise of a human.”
One challenge is that ChatGPT's responses are based on the data on which it was trained, which may result in biased or inaccurate information.
“One challenge is that the responses of ChatGPT are based on the data on which it was trained, which may result in biased or inaccurate information.”
ChatGPT can assist in drug discovery, research proposal writing, and summarising complex medical research, expediting the research process.
“It can assist in drug discovery, research proposal writing, and summarising complex medical research, expediting the research process [11,24,34,35,36,37,38].”
In pharmaceutical research, ChatGPT can contribute by sifting through vast volumes of scientific literature, identifying potential drug candidates, and suggesting innovative research directions.
“In the realm of pharmaceutical research, ChatGPT can contribute by sifting through vast volumes of scientific literature, identifying potential drug candidates, and suggesting innovative research directions.”
Cites
Privacy in the age of medical big data
Price, W. N., & Cohen, I. G. (2019) · Nature Medicine · doi:10.1038/s41591-018-0272-7 · Cited by 1,522 · see citing works
On Defining Artificial Intelligence
Wang, P. (2019) · Journal of Artificial General Intelligence · doi:10.2478/jagi-2019-0002 · Cited by 740 · see citing works
Hopkins, A. M., Logan, J. M., Kichenadasse, G., & Sorich, M. J. (2023) · JNCI Cancer Spectrum · doi:10.1093/jncics/pkad010 · Cited by 259 · see citing works
Artificial intelligence and robotics: a combination that is changing the operating room
Andras, I., Mazzone, E., van Leeuwen, F. W. B., De Naeyer, G., van Oosterom, M. N., Beato, S., Buckle, T., O’Sullivan, S., van Leeuwen, P. J., Beulens, A., et al. (2020) · World Journal of Urology · doi:10.1007/s00345-019-03037-6 · Cited by 153 · see citing works
Crossnohere, N. L., Elsaid, M. I., Paskett, J., Bose‐Brill, S., & Bridges, J. F. P. (2022) · Journal of Medical Internet Research · doi:10.2196/36823 · Cited by 131 · see citing works
Stam, W. T., Goedknegt, L. K., Ingwersen, E. W., Schoonmade, L. J., Bruns, E. R. J., & Daams, F. D. (2021) · Surgery · doi:10.1016/j.surg.2021.10.002 · Cited by 95 · see citing works
Yang, S., Lee, J., Sezgın, E., Bridge, J. A., & Lin, S. M. (2020) · JMIR mhealth and uhealth · doi:10.2196/24045 · Cited by 69 · see citing works
Feng, B., Ma, X., Wang, S., Cai, W., Liu, X., & Zhao, X. (2021) · World Journal of Gastroenterology · doi:10.3748/wjg.v27.i32.5341 · Cited by 33 · see citing works
Factors Associated with Information Breach in Healthcare Facilities: A Systematic Literature Review
Khanijahani, A., Iezadi, S., Agoglia, S., et al. (2022) · Journal of Medical Systems · doi:10.1007/s10916-022-01877-1 · Cited by 17 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Haltaufderheide, J., & Ranisch, R. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01157-x · Cited by 396 · see citing works
Younis, H. A., Eisa, T. A. E., Nasser, M., Sahib, T. M., Noor, A. A., Alyasiri, O. M., Salisu, S., Hayder, I. M., & Younis, H. A. (2024) · Diagnostics · doi:10.3390/diagnostics14010109 · Cited by 242 · see citing works
- Authors
- Kavian, J. A., Wilkey, H. L., Patel, P. A., & Boyd, C. J.
- Affiliations
- NYU Langone Health (US)
- Augusta University Health (US)
- Corresponding author
- Kavian, Joseph A.
- Venue
- The American Surgeon™
- Publisher
- SAGE Publications
- Published
- 2023-05-06
- Volume
- 89
- Issue
- 12
- Pages
- 5102-5104
- ISSN
- 0003-1348 (ISSN-L)
- 1555-9823
- OpenAlex
- W4372342904
- Cited by
- 35
- References
- 9
- Citations by year
- 2026: 9 · 2025: 7 · 2024: 13 · 2023: 6
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The American Surgeon (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Surgery › Surgical Simulation and Training
- Keywords
- artificial intelligence in surgery, ChatGPT, AI ethics, patient safety, preoperative diagnosis, intraoperative technique, postoperative complications, patient data privacy
- MeSH terms
- Artificial Intelligence, Humans, Medicine
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