Addressing the Rhino in the Room: ChatGPT Creates "Novel" Patent Ideas for Rhinoplasty
Najafali D., Galbraith LG., Camacho JM., Arnold SH., Alperovich M., King TW.
Laboratory Study, published in Eplasty (2024) — summary generated from the PubMed abstract.
Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.
- Level A · Stronger Clinical Evidence
- Level B · Emerging clinical evidence with positive signals
- Level C · Early human research exploring benefits
- Level D · Scientific groundwork from lab and animal studies
- Emerging · Emerging topic under active research
This page is generated from the PubMed record. The Thai description is an automated summary of bibliographic fields and the abstract, not a full translation, and is not medical advice.
- Study type
- Laboratory Study
- Journal
- Eplasty (2024)
- Reported sample size
- —
- Source database
- Europe PMC
- PMID
- 38685992
- PMCID
- PMC11056627
- Citations
- 4
Abstract (original English)
Background OpenAI's ChatGPT can generate novel ideas for a number of applications. The aim of this study was to prompt the chatbot to generate possible innovations in aesthetic surgery relating to rhinoplasty. Methods ChatGPT was prompted to develop rhinoplasty patents. The resulting outputs were tabulated and categorized based on technology domain and anatomic location. A Google Patents search was conducted to find uses of the term "rhinoplasty" between 2021 and 2023. Patents not pertaining to rhinoplasty were excluded. Filed patents were compared with those generated by ChatGPT to determine predictive power. Results A total of 40 patents resulted from ChatGPT and 42 Google Patents from 2021 to 2023 were included. Patents generated without a detailed description command were related to preoperative planning (35%), intraoperative tools (30%), functional evaluation (15%), and 3D printing and implants (10%). Patents with a detailed description command resulted in the majority being postoperative tools (40%), followed by intraoperative tools (30%), 3D printing and implants (10%), and nonsurgical (10%) categories. The anatomic locations included the airway, dorsum, septum, and nasal tip. ChatGPT's predictive power yielded 45% for the detailed prompting, which was higher than the prompt without the detail command. Conclusions ChatGPT has reasonable potential to generate ideas for in
What this study does not prove
- • This study does not prove SVF is an approved treatment or a replacement for standard care.
- • This is preclinical work; animal or laboratory results cannot be applied to humans.
Evidence level
Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.
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