Facial Analysis for Plastic Surgery in the Era of Artificial Intelligence: A Comparative Evaluation of Multimodal Large Language Models.
人工智慧時代的整形外科臉部分析:多模態大型語言模型的比較性評估
J Clin Med 2025-05-28
Comparative Analysis of Large Language Models in Emergency Plastic Surgery Decision-Making: The Role of Physical Exam Data.
緊急整形外科決策中大型語言模型的比較分析:身體檢查數據的作用。
J Pers Med 2024-06-27
Evaluating Large Language Model (LLM) Performance on Established Breast Classification Systems.
評估大型語言模型 (LLM) 在既定乳腺分類系統上的表現。
Diagnostics (Basel) 2024-07-27
Comparative Performance of the Leading Large Language Models in Answering Complex Rhinoplasty Consultation Questions.
大型語言模型在回答複雜鼻整形諮詢問題中的比較表現。
Facial Plast Surg Aesthet Med 2025-01-15
Assessing the Informational Value of Large Language Models Responses in Aesthetic Surgery: A Comparative Analysis with Expert Opinions.
評估大型語言模型在美學手術中回應的資訊價值:與專家意見的比較分析。
Aesthetic Plast Surg 2025-02-18
Initial Proof-of-Concept Study for a Plastic Surgery Specific Artificial Intelligence Large Language Model: PlasticSurgeryGPT.
針對整形外科特定人工智慧大型語言模型的初步概念驗證研究:PlasticSurgeryGPT。
Aesthet Surg J 2025-04-08
Evaluating Large Language Model's accuracy in current procedural terminology coding given operative note templates across various plastic surgery sub-specialties.
針對不同整形外科次專科手術紀錄範本,評估大型語言模型於Current Procedural Terminology (CPT) 編碼的準確性
J Plast Reconstr Aesthet Surg 2025-05-14
The Current Landscape of Artificial Intelligence in Plastic Surgery Education and Training: A Systematic Review.
整形外科教育與訓練中人工智慧的現況:系統性回顧
J Surg Educ 2025-05-16
Artificial Intelligence and Human Expertise in Cleft Lip and Palate Care: A Comparative Study of Accuracy, Readability, and Treatment Quality.
人工智慧與人類專家於唇顎裂照護中的應用:準確性、可讀性與治療品質之比較研究
J Craniofac Surg 2025-06-17
Synthetic Patient-Physician Conversations Simulated by Large Language Models: A Multi-Dimensional Evaluation.
由大型語言模型模擬的虛擬醫病對話:多面向評估
Sensors (Basel) 2025-07-30
這項研究比較四款主流大型語言模型在產生整形外科醫病對話的表現,結果顯示它們都能產生真實又實用的對話,平均分數都超過4.5分。雖然 Gemini Pro 2.5 和 Claude 3.7 Sonnet 表現稍好,但彼此間沒有明顯差異。這些模型適合用於醫學教育和研究,但還是要注意多元性和偏見的問題。
PubMedDOI