Linfang Deng, Tianyi Wang, Yangzhang, Zhenhua Zhai, Wei Tao, Jincheng Li, Yi Zhao, Shaoting Luo, Jinjiang Xu
BACKGROUND: Large language models (LLMs) have garnered significant attention in the AI domain owing to their exemplary context recognition and response capabilities. However, the potential of LLMs in specific clinical scenarios, particularly in breast cancer diagnosis, treatment, and care, has not been fully explored. This study aimed to compare the performances of three major LLMs in the clinical context of breast cancer. METHODS: In this study, clinical scenarios designed specifically for breast cancer were segmented into five pivotal domains (nine cases): assessment and diagnosis, treatment decision-making, postoperative care, psychosocial support, and prognosis and rehabilitation...
April 1, 2024: International Journal of Surgery