理解力
Lift(数据挖掘)
人工智能
计算机科学
医学物理学
外科
医学
机器学习
程序设计语言
作者
Ryan S. Huang,Michael Balas,F. Yan,Allan E. Wulc
标识
DOI:10.1097/prs.0000000000011860
摘要
Summary: Text-to-image models powered by artificial intelligence offer a promising tool for enhancing patients’ comprehension of cosmetic surgery outcomes and providing personalized visual forecasts of their appearance after the procedure. This study explores the efficacy of text-to-image AI models, specifically DALL·E2, in improving preoperative counseling for patients undergoing lip-lift procedures. Preoperative photographs of 4 patients, who had given their consent, were processed using DALL·E2, which allows users to modify specific areas of an image and input text descriptions to visualize anticipated changes. The authors successfully demonstrated the ability of DALL·E2 to generate accurate visual predictions within a short timeframe of 2 minutes. Selected images provided realistic expectations of the postoperative appearance, aiding in better patient understanding and expectation management.
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