Future Perspective of Risk Prediction in Aesthetic Surgery: Is Artificial Intelligence Reliable?

Author:

Duran Alpay,Cortuk Oguz,Ok Bora

Abstract

Abstract Background Artificial intelligence (AI) techniques are showing significant potential in the medical field. The rapid advancement in artificial intelligence methods suggests their soon-to-be essential role in physicians’ practices. Objectives In this study, we sought to assess and compare the readability, clarity, and precision of medical knowledge responses provided by 3 large language models (LLMs) and informed consent forms for 14 common aesthetic surgical procedures, as prepared by the American Society of Plastic Surgeons (ASPS). Methods The efficacy, readability, and accuracy of 3 leading LLMs, ChatGPT-4 (OpenAI, San Francisco, CA), Gemini (Google, Mountain View, CA), and Copilot (Microsoft, Redmond, WA), was systematically evaluated with 14 different prompts related to the risks of 14 common aesthetic procedures. Alongside these LLM responses, risk sections from the informed consent forms for these procedures, provided by the ASPS, were also reviewed. Results The risk factor segments of the combined general and specific operation consent forms were rated highest for medical knowledge accuracy (P < .05). Regarding readability and clarity, the procedure-specific informed consent forms, including LLMs, scored highest scores (P < .05). However, these same forms received the lowest score for medical knowledge accuracy (P < .05). Interestingly, surgeons preferred patient-facing materials created by ChatGPT-4, citing superior accuracy and medical information compared to other AI tools. Conclusions Physicians prefer patient-facing materials created by ChatGPT-4 over other AI tools due to their precise and comprehensive medical knowledge. Importantly, adherence to the strong recommendation of ASPS for signing both the procedure-specific and the general informed consent forms can avoid potential future complications and ethical concerns, thereby ensuring patients receive adequate information.

Publisher

Oxford University Press (OUP)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Humans‐written versus ChatGPT‐generated case reports;Journal of Obstetrics and Gynaecology Research;2024-09-06

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