Aesthetic Surgery Advice and Counseling from Artificial Intelligence: A Rhinoplasty Consultation with ChatGPT
Open accessAbstract
BACKGROUND: ChatGPT is an open-source artificial large language model that uses deep learning to produce human-like text dialogue. This observational study evaluated the ability of ChatGPT to provide informative and accurate responses to a set of hypothetical questions designed to simulate an initial consultation about rhinoplasty. METHODS: Nine questions were prompted to ChatGPT on rhinoplasty. The questions were sourced from a checklist published by the American Society of Plastic Surgeons, and the responses were assessed for accessibility, informativeness, and accuracy by Specialist Plastic Surgeons with extensive experience in rhinoplasty. RESULTS: ChatGPT was able to provide coherent and easily comprehensible answers to the questions posed, demonstrating its understanding of natural language in a health-specific context. The responses emphasized the importance of an individualized approach, particularly in aesthetic plastic surgery. However, the study also highlighted ChatGPT's limitations in providing more detailed or personalized advice. CONCLUSION: Overall, the results suggest that ChatGPT has the potential to provide valuable information to patients in a medical context, particularly in situations where patients may be hesitant to seek advice from medical professionals or where access to medical advice is limited. However, further research is needed to determine the scope and limitations of AI language models in this domain and to assess the potential benefits and risks associated with their use. LEVEL OF EVIDENCE V: Observational study under respected authorities. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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ChatGPT can offer standardised and accurate responses that prepare patients for consultations and help them make informed decisions.
“ChatGPT can offer standardised and accurate responses, which prepare patients for their consultations and help them make informed decisions [5,6,7,8,9,10,42,43].”
ChatGPT can function as a virtual assistant, offering patients crucial preoperative information for cosmetic orthognathic surgery.
“Within the realm of surgical procedures, such as cosmetic orthognathic surgery, ChatGPT can function as a virtual assistant, offering patients crucial preoperative information.”
ChatGPT can be used in pandemic management, surgical consultations, dental practices, medical education, disease diagnosis, cellular imaging, sonar imaging, radiology, and pharmaceutical research.
“It was used in all areas: healthcare and management [5,6,7,8,9], aiding cosmetic orthognathic surgery consultation [10], revolutionising dental practices [8,11,12], medical scientific articles and education fields [6,9,13,14,15,16,17,18,19,20,21,22,23], support in disease diagnosis [24], revolutionising radiology, sonar imaging and writing assessment [13,25,26,27,28,29,30,31,32,33], pharmaceutical”
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Cites
Dermatologist-level classification of skin cancer with deep neural networks
Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017) · Nature · doi:10.1038/nature21056 · Cited by 14,362 · see citing works
Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2023) · JMIR Medical Education · doi:10.2196/45312 · Cited by 2,078 · see citing works
Overview of artificial intelligence in medicine
Amisha, Malik, P., Pathania, M., & Rathaur, V. K. (2019) · Journal of Family Medicine and Primary Care · doi:10.4103/jfmpc.jfmpc_440_19 · Cited by 1,106 · cited 1× · see citing works
“most aspects of modern life and have seen increasing utilization in the medical field [11].”
What ChatGPT and generative AI mean for science
Stokel-Walker, C., & Van Noorden, R. (2023) · Nature · doi:10.1038/d41586-023-00340-6 · Cited by 828 · see citing works
Zhou, N., Zhang, C., Lv, H., Hao, C.-X., Li, T., Zhu, J., Zhu, H., Jiang, M., Liu, K.-W., Hou, H., et al. (2018) · The Oncologist · doi:10.1634/theoncologist.2018-0255 · Cited by 212 · see citing works
ChatGPT and antimicrobial advice: the end of the consulting infection doctor?
Howard, A., Hope, W., & Gerada, A. (2023) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(23)00113-5 · Cited by 202 · see citing works
The Central Role of the Nose in the Face and the Psyche: Review of the Nose and the Psyche
Amodeo, C. A. (2007) · Aesthetic Plastic Surgery · doi:10.1007/s00266-006-0241-2 · Cited by 136 · see citing works
Artificial Intelligence in Clinical Health Care Applications: Viewpoint
van Hartskamp, M., Consoli, S., Verhaegh, W., Petković, M., & van de Stolpe, A. (2019) · Interactive Journal of Medical Research · doi:10.2196/12100 · Cited by 126 · see citing works
Patient satisfaction following rhinoplasty
Guyuron, B., & Bokhari, F. (1996) · Aesthetic Plastic Surgery · doi:10.1007/bf02275535 · Cited by 95 · see citing works
Risks and complications in rhinoplasty.
Rettinger, G. (2007) · PubMed · Cited by 77 · see citing works
Guyuron, B. (2000) · Plastic & Reconstructive Surgery · doi:10.1097/00006534-200005000-00057 · Cited by 71 · see citing works
Kurian, N., Cherian, J. M., Sudharson, N. A., Varghese, K. G., & Wadhwa, S. (2023) · BDJ · doi:10.1038/s41415-023-5461-1 · Cited by 65 · see citing works
Cafferty, A., & Becker, D. G. (2015) · Clinics in Plastic Surgery · doi:10.1016/j.cps.2015.09.002 · Cited by 49 · see citing works
Afifi, A. M., Kempton, S. J., Gordon, C. R., Pryor, L. S., Khalil, A. A., Sweeney, W. M., Kusuma, S., Langevin, C.-J., & Zins, J. E. (2015) · Aesthetic Plastic Surgery · doi:10.1007/s00266-015-0449-0 · Cited by 25 · see citing works
Digital approach to informed consent in bariatric surgery: a randomized controlled trial
Zevin, B., Almakky, M., Mancini, U., et al. (2021) · Surgical Endoscopy · doi:10.1007/s00464-020-08277-x · Cited by 18 · see citing works
Kalaaji, A., Dreyer, S., Schnegg, J., Sanosyan, L., Radovic, T., & Marić, I. (2019) · Plastic and Reconstructive Surgery, Global Open · doi:10.1097/gox.0000000000002448 · Cited by 18 · see citing works
Digital Informed Consent: Modernising Information Sharing in Surgery to Empower Patients
Parsons, S. L., Daliya, P., Evans, P., et al. (2022) · World Journal of Surgery · doi:10.1007/s00268-022-06846-w · Cited by 10 · see citing works
Novel Selection Tools in Rhinoplasty Patients
Lekakis, G., Constantian, M. B., Most, S. P., Picavet, V. A., & Hellings, P. W. (2022) · Facial Plastic Surgery · doi:10.1055/s-0042-1748314 · Cited by 4 · see citing works
Flagged first, then by citations
Research works printed but not linked: 3
- [17]World Health Organization (2010) Increasing access to health workers in remote and rural areas through improved retention: global policy recommendations 23741785
- [19]Fichman M, Pedra Buena IT (2023) Rhinoplasty. StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK558970/ 32644396
- [20]Amodeo CA The central role of the nose in the face and the psyche: review of the nose and the psyche Aesthetic Plast Surg 2007 31 406 410 10.1007/s00266-006-0241-2 17551776 · DOI
Cited by
Sorted by citations
Current applications and challenges in large language models for patient care: a systematic review
Busch, F., Hoffmann, L., Rueger, C., van Dijk, E. H., Kader, R., Ortiz-Prado, E., Makowski, M. R., Saba, L., Hadamitzky, M., Kather, J. N., et al. (2025) · Communications Medicine · doi:10.1038/s43856-024-00717-2 · Cited by 358 · see citing works
Large Language Models for Chatbot Health Advice Studies: A Systematic Review
Huo, B., Boyle, A., Marfo, N., Tangamornsuksan, W., Steen, J. P., McKechnie, T., Lee, Y., Mayol, J., Antoniou, S. A., Thirunavukarasu, A. J., et al. (2025) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.57879 · Cited by 283 · 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
Akiba, D., & Fraboni, M. C. (2023) · Education Sciences · doi:10.3390/educsci13090885 · Cited by 115 · see citing works
Safety of Large Language Models in Addressing Depression
Heston, T. F. (2023) · Cureus · doi:10.7759/cureus.50729 · Cited by 61 · see citing works
Buzzaccarini, G., Degliuomini, R. S., & Borin, M. (2023) · Aesthetic Plastic Surgery · doi:10.1007/s00266-023-03416-w · Cited by 42 · see citing works
ChatGPT for diabetes education: potential, accuracy, and accessibility in patient support
Abuzar, M., Rai, S., Pathan, T., Fakki, F., & Syed, S. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1768843 · Cited by 4 · see citing works
- Authors
- Xie, Y., Seth, I., Hunter-Smith, D. J., Rozen, W. M., Ross, R., & Lee, M.
- Affiliations
- Peninsula Health (AU)
- Corresponding author
- Seth, Ishith
- Venue
- Aesthetic Plastic Surgery
- Published
- 2023-04-24
- Volume
- 47
- Issue
- 5
- Pages
- 1985-1993
- ISSN
- 0364-216X (ISSN-L)
- 1432-5241
- PMC
- PMC10581928
- OpenAlex
- W4366823098
- Cited by
- 198
- References
- 18
- Citations by year
- 2026: 33 · 2025: 49 · 2024: 76 · 2023: 40
- FWCI
- 7.88
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Aesthetic Plastic Surgery (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Monash University
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Surgery › Nasal Surgery and Airway Studies
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- ChatGPT, large language models, artificial intelligence, rhinoplasty, patient counseling, preoperative consultation, patient-provider communication, AI-generated medical advice, AI response accuracy
- MeSH terms
- Artificial Intelligence, Counseling, Esthetics, Humans, Referral and Consultation, Rhinoplasty, Surgery, Plastic
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