甲状腺手术术前决策中ChatGPT-4o、Gemini Advanced与DeepSeek R1的比较评估

数据集获取（Figshare）

• 源站标题：Table 1_ChatGPT-4o, Gemini Advanced and DeepSeek R1 in preoperative decision-making for thyroid surgery: a comparative assessment with human surgeons.xlsx
• DOI：10.3389/fonc.2025.1590230.s001
• 发布日期：2025-10-24
• 文件数：1 个
• 文件总体积：68.76 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_1_ChatGPT-4o_Gemini_Advanced_and_DeepSeek_R1_in_preoperative_decision-making_for_thyroid_surgery_a_comparative_assessment_with_human_surgeons_xlsx/30435487

命令行下载

curl -L -o "Table 1_ChatGPT-4o, Gemini Advanced and DeepSeek R1 in preoperative decision-making for thyroid surgery: a comparative assessment with human surgeons.xlsx" "https://ndownloader.figshare.com/files/59004292"

文件清单

• Table 1_ChatGPT-4o, Gemini Advanced and DeepSeek R1 in preoperative decision-making for thyroid surgery: a comparative assessment with human surgeons.xlsx（68.76 KB）

文件总体积 68.76 KB（源站 API 实测）。

数据说明

The integration of large language models (LLMs) into surgical decision-making is an emerging field with potential clinical value. This study assessed the preoperative decision-making consistency of ChatGPT-4o, Gemini Advanced, and DeepSeek R1 in comparison with expert consensus, using clinical data from 123 patients undergoing thyroid surgery. Overall concordance rates were 47.97% for ChatGPT-4o, 24.39% for Gemini Advanced, and 56.10% for DeepSeek R1. In thyroidectomy extent decisions, all three models showed moderate consistency with the surgical team, with agreement rates of 61.79% (κ=0.484) for ChatGPT-4o, 67.48% (κ=0.548) for Gemini, and 67.48% (κ=0.535) for DeepSeek R1 (all p < 0.001). However, significant divergence was observed in lymph node dissection planning: ChatGPT-4o achieved a high concordance rate of 69.11% (κ=0.616), DeepSeek R1 showed the highest at 79.67% (κ=0.741), while Gemini’s performance was relatively poor at 34.96% (κ=0.188). Though our findings demonstrate that ChatGPT-4o and DeepSeek R1 exhibit substantial agreement with experienced surgeons in preoperative planning, overall performance still leaves room for improvement. Nevertheless, model-specific variability—particularly in oncologic decision-making—highlights the need for refinement and robust clinical validation before widespread clinical adoption.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fonc.2025.1590230.s001（source: https://frontiersin.figshare.com/articles/dataset/Table_1_ChatGPT-4o_Gemini_Advanced_and_DeepSeek_R1_in_preoperative_decision-making_for_thyroid_surgery_a_comparative_assessment_with_human_surgeons_xlsx/30435487）。