Assessment of the proficiency of ChatGPT-4o in an image-based robot-assisted radical prostatectomy scenario.
Abstract
423 Background: Surgery is a process that heavily relies on complex visual information. Many AI-based surgical teaching and assistance applications have emerged. However, the application of the newly released ChatGPT-4o in surgical contexts remains unexplored. This study aims to investigate the ability of ChatGPT-4o in analyzing and recognizing anatomical structures, surgical procedures, and operational precautions based on image information in a surgical context. Utilizing screenshots from robot-assisted radical prostatectomy videos sourced from the internet. Methods: We developed a test comprising 77 images and 65 questions, with a total score of 100 points. The test includes sections on anatomical structures, surgical procedures, and operational precautions. We sequentially input the questions into the ChatGPT-4o model and employed strategies to enhance its performance during the test. A passing score was set at 60 points or above, and an excellent score at 80 points or above. Results: ChatGPT-4o achieved a score of 68, surpassing the passing threshold. The accuracy for non-image questions was higher than for image-based questions (85.71% vs. 58.46%, χ² = 7.78, p = 0.005), and questions with fewer images had a higher accuracy than those with multiple images (71.11% vs. 30.00%, p < 0.001). Furthermore, we found ChatGPT-4o performed differently in recognizing different structures, with the highest accuracy for questions involving muscle and fascia (100%) and the lowest for those involving nerve and vessel structures (33.33%). Conclusions: ChatGPT demonstrated commendable abilities in image recognition and problem analysis in surgical contexts. We hope that the results of this study will contribute to future applications of ChatGPT in AI-assisted surgical teaching and assistance.
Article Details
Journal Info
Journal of Clinical Oncology
Lippincott Williams & Wilkins
Authors (6)
Jiakun Li
State Key Laboratory of Chemo and Biosensing, College of Chemistry and Chemical Engineering
Jing Zhao
Zeqi Wang
West China Hospital, Sichuan University, Chengdu, China
Le Tong
Bairong Shen
West China Hospital, Chengdu, China
Qiang Wei
Shenzhen Geim Graphene Center, Shenzhen Key Laboratory of Advanced Layered Materials for Value-added Applications, Tsinghua-Berkeley Shenzhen Institute and Institute of Materials Research