聊天机器人与传统资源在干眼症患者教育中的有效性评估

数据集获取（Figshare）

• 源站标题：Evaluating the effectiveness of chatbots and traditional resources in patient education on dry eye disease
• DOI：10.6084/m9.figshare.29413948.v1
• 发布日期：2025-06-26
• 文件数：2 个
• 文件总体积：148.72 KB
• 源站页面：https://tandf.figshare.com/articles/dataset/Evaluating_the_effectiveness_of_chatbots_and_traditional_resources_in_patient_education_on_dry_eye_disease/29413948

命令行下载

curl -L -o "tceo_a_2517750_sm0952.docx" "https://ndownloader.figshare.com/files/55681222"
curl -L -o "tceo_a_2517750_sm0951.docx" "https://ndownloader.figshare.com/files/55681225"

文件清单

• tceo_a_2517750_sm0952.docx（128.31 KB）
• tceo_a_2517750_sm0951.docx（20.41 KB）

文件总体积 148.72 KB（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

Artificial intelligence chatbots demonstrate potential as valuable educational resources for patients with dry eye disease, offering complementary information to established medical platforms.
The increasing prevalence of dry eye disease necessitates reliable and comprehensible patient information resources. This study evaluates and compares the quality of information provided by contemporary AI chatbots with established ophthalmological sources.
Three leading AI chatbots (ChatGPT-3.5, Gemini, and Llama) and the American Academy of Ophthalmology (AAO) website were systematically evaluated using 20 common patient questions about dry eye disease. Responses were assessed for accuracy using the Structure of Observed Learning Outcome (SOLO) taxonomy, understandability and actionability using the Patient Education Materials Assessment Tool (PEMAT), and linguistic accessibility using Flesch-Kincaid readability metrics.
Gemini demonstrated superior understandability with a mean PEMAT-U score of 73.4 ± 11.4, significantly higher than ChatGPT (65.4 ± 10.6), Llama (63.4 ± 10.3), and AAO (52.5 ± 19.3) (p p = 0.120). The AAO website exhibited the highest reading ease score (50.4 ± 17.9, p = 0.015). For accuracy assessment, ChatGPT achieved the highest mean SOLO score (3.4 ± 0.7), followed closely by Gemini (3.3 ± 0.8), with no significant performance differences detected among chatbots (p = 0.574). No instances of incorrect or potentially harmful information were identified across any evaluated source.
While AI chatbots demonstrate promising capabilities for patient education in dry eye disease, particularly in providing comprehensive and understandable information, their higher linguistic complexity presents a potential accessibility barrier. Future development should focus on enhancing readability while maintaining comprehensive content, positioning chatbots as valuable complements to – rather than replacements for – professional medical consultation.

许可

CC BY

引用

学术使用请引用 DOI 10.6084/m9.figshare.29413948.v1（source: https://tandf.figshare.com/articles/dataset/Evaluating_the_effectiveness_of_chatbots_and_traditional_resources_in_patient_education_on_dry_eye_disease/29413948）。