白内障手术并发症对话指南

数据集获取（Figshare）

• 源站标题：Conversational Guide for Cataract Surgery Complications: A Comparative Study of Surgeons versus Large Language Model-Based Chatbot Generated Instructions for Patient Interaction
• DOI：10.6084/m9.figshare.28716210.v1
• 发布日期：2025-04-02
• 文件数：2 个
• 文件总体积：2.53 MB
• 源站页面：https://tandf.figshare.com/articles/dataset/Conversational_Guide_for_Cataract_Surgery_Complications_A_Comparative_Study_of_Surgeons_versus_Large_Language_Model-Based_Chatbot_Generated_Instructions_for_Patient_Interaction/28716210

命令行下载

curl -L -o "iope_a_2484772_sm9618.tiff" "https://ndownloader.figshare.com/files/53378931"
curl -L -o "iope_a_2484772_sm9603.docx" "https://ndownloader.figshare.com/files/53378934"

文件清单

• iope_a_2484772_sm9618.tiff（2.51 MB）
• iope_a_2484772_sm9603.docx（19.43 KB）

文件总体积 2.53 MB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

It is difficult to explain the complications of surgery to patients. Care has to be taken to convey the facts clearly and objectively while expressing concern for their wellbeing. This study compared responses from surgeons with responses from a large language model (LLM)-based chatbot.
We presented 10 common scenarios of cataract surgery complications to seven senior surgeons and a chatbot. The responses were graded by two independent graders for comprehension, readability, and complexity of language using previously validated indices. The responses were analyzed for accuracy and completeness. Honesty and empathy were graded for both groups. Scores were averaged and tabulated.
The readability scores for the surgeons (10.64) were significantly less complex than the chatbot (12.54) (p p = 0.164). The responses from the chatbot were more generalized, lacking specific alternative measures. While empathy scores were higher for surgeons (1.81 vs. 1.20, p = 0.041), honesty scores showed no significant difference.
The LLM-based chatbot gave a detailed description of the complication but was less specific about the alternative measures. The surgeons had a more in-depth understanding of the situation. The chatbot showed complete honesty but scored less for empathy. With more training using complex real-world scenarios and specialized ophthalmologic data, the chatbots could be used to assist the surgeons in counselling patients for postoperative complications.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.28716210.v1（source: https://tandf.figshare.com/articles/dataset/Conversational_Guide_for_Cataract_Surgery_Complications_A_Comparative_Study_of_Surgeons_versus_Large_Language_Model-Based_Chatbot_Generated_Instructions_for_Patient_Interaction/28716210）。