Lim Bryan, Seth Ishith, Kah Skyler, Sofiadellis Foti, Ross Richard J, Rozen Warren M, Cuomo Roberto
Department of Plastic and Reconstructive Surgery, Peninsula Health, Frankston, VIC 3199, Australia.
Central Clinical School, Faculty of Medicine, Monash University, Melbourne, VIC 3004, Australia.
J Clin Med. 2023 Oct 14;12(20):6524. doi: 10.3390/jcm12206524.
Artificial intelligence (AI), notably Generative Adversarial Networks, has the potential to transform medical and patient education. Leveraging GANs in medical fields, especially cosmetic surgery, provides a plethora of benefits, including upholding patient confidentiality, ensuring broad exposure to diverse patient scenarios, and democratizing medical education. This study investigated the capacity of AI models, DALL-E 2, Midjourney, and Blue Willow, to generate realistic images pertinent to cosmetic surgery. We combined the generative powers of ChatGPT-4 and Google's BARD with these GANs to produce images of various noses, faces, and eyelids. Four board-certified plastic surgeons evaluated the generated images, eliminating the need for real patient photographs. Notably, generated images predominantly showcased female faces with lighter skin tones, lacking representation of males, older women, and those with a body mass index above 20. The integration of AI in cosmetic surgery offers enhanced patient education and training but demands careful and ethical incorporation to ensure comprehensive representation and uphold medical standards.
人工智能（AI），尤其是生成对抗网络（GAN），有潜力改变医学和患者教育。在医学领域，特别是整形外科中利用GAN有诸多益处，包括维护患者隐私、确保广泛接触各种患者场景以及使医学教育民主化。本研究调查了人工智能模型DALL-E 2、Midjourney和Blue Willow生成与整形外科相关逼真图像的能力。我们将ChatGPT-4和谷歌的BARD的生成能力与这些GAN相结合，以生成各种鼻子、面部和眼睑的图像。四位获得董事会认证的整形外科医生对生成的图像进行了评估，从而无需真实患者照片。值得注意的是，生成的图像主要展示的是肤色较浅的女性面部，缺乏男性、老年女性以及体重指数高于20的人群的代表。人工智能在整形外科中的整合提供了更好的患者教育和培训，但需要谨慎且符合道德地纳入，以确保全面代表性并维护医学标准。
