数据表1_导航胰腺移植认知：使用AI驱动分析评估公众情感和策略
关于胰腺移植公众认知的AI驱动分析补充数据表，评估网站情感、共识、可读性并提数字健康传播策略。
基本信息
资源简介
数据表1_导航胰腺移植认知：使用AI驱动分析评估公众情感和策略
【一句话概览】
本数据集是 figshare 公开的文本数据集，收录 1 个文件、合计 687.12 KB，主题涵盖 pancreas transplantation、public perception、digital health communication、sentiment analysis、connected health，可用于医学自然语言处理（实体识别、信息抽取等），CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《Data Sheet 1_Navigating pancreas transplant perceptions: assessing public sentiment and strategies using AI-driven analysis.docx》。配套论文《Impact of Pancreas Transplantation on the Quality of Life of Diabetic Renal Transplant Recipients》发表于 Transplantation Proceedings（2009），DOI：10.1016/j.transproceed.2009.07.101。源站首次发布：2024-11-29。
【数据内容】
源站原始描述：BackgroundPancreas transplantation, a crucial treatment for diabetes, is underutilized due to its invasiveness, strict criteria, organ scarcity, and limited centers. This highlights the need for enhanced public education and awareness through digital health platforms. MethodsWe utilized Google''s AI-driven, consensus-based model and Claude AI 3.0 Opus by Anthropic to analyze public perceptions of pancreas transplantation. The top 10 websites identified by Google as of April-May 2024 were reviewed…
【数据结构与技术规格】
文件数 1 个，合计 687.12 KB。Data Sheet 1_Navigating pancreas transplant perceptions: assessing public sentiment and strategies using AI-driven analysis.docx：application/vnd.openxmlformats-officedocument.wordprocessingml.document，687.12 KB。数据集 DOI：10.3389/fdgth.2024.1453341.s001。
【主题与分类】
源站学科分类：Health Informatics。主题标签：pancreas transplantation、public perception、digital health communication、sentiment analysis、connected health、AI-driven analysis。
【适用方向】
文本类数据可用于医学自然语言处理，如命名实体识别、信息抽取与文本分类。
【获取与许可】
源站页面：https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Navigating_pancreas_transplant_perceptions_assessing_public_sentiment_and_strategies_using_AI-driven_analysis_docx/27929280
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Valencia, Oscar A. Garcia; Thongprayoon, Charat; Jadlowiec, Caroline C.; Mao, Shennen A.; Miao, Jing; Leeaphorn, Napat; et al. (2024). Data Sheet 1_Navigating pancreas transplant perceptions: assessing public sentiment and strategies using AI-driven analysis.docx. Frontiers. Dataset
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载，适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档，适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务（收技术服务费，非数据销售）
暂未开放当前数据集主要来源为 Kaggle 公开托管，完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取（Figshare）
- 源站标题：Data Sheet 1_Navigating pancreas transplant perceptions: assessing public sentiment and strategies using AI-driven analysis.docx
- DOI：10.3389/fdgth.2024.1453341.s001
- 发布日期：2024-11-29
- 文件数：1 个
- 文件总体积：687.12 KB
- 源站页面：https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Navigating_pancreas_transplant_perceptions_assessing_public_sentiment_and_strategies_using_AI-driven_analysis_docx/27929280
命令行下载
curl -L -o "Data Sheet 1_Navigating pancreas transplant perceptions: assessing public sentiment and strategies using AI-driven analysis.docx" "https://ndownloader.figshare.com/files/50874846"
文件清单
Data Sheet 1_Navigating pancreas transplant perceptions: assessing public sentiment and strategies using AI-driven analysis.docx（687.12 KB）
文件总体积 687.12 KB（源站 API 实测）。
数据说明
BackgroundPancreas transplantation, a crucial treatment for diabetes, is underutilized due to its invasiveness, strict criteria, organ scarcity, and limited centers. This highlights the need for enhanced public education and awareness through digital health platforms.
MethodsWe utilized Google’'s AI-driven, consensus-based model and Claude AI 3.0 Opus by Anthropic to analyze public perceptions of pancreas transplantation. The top 10 websites identified by Google as of April-May 2024 were reviewed, focusing on sentiment, consensus, content readability, and complexity to develop strategies for better public engagement and understanding using digital health technologies.
ResultsThe top 10 websites, originating from the US and UK, showed a neutral and professional tone, targeting medical professionals and patients. Complex content was updated between 2021 and 2024, with a readability level suitable for high school to early college students. AI-driven analysis revealed strategies to increase public interest and understanding, including incorporating patient stories, simplifying medical jargon, utilizing visual aids, emphasizing quality of life improvements, showcasing research progress, facilitating patient outreach, promoting community engagement, partnering with influencers, and regularly updating content through digital health platforms.
ConclusionTo increase interest in pancreas transplantation in the era of connected health, we recommend integrating real patient experiences, simplifying medical content, using visual explanations, emphasizing post-transplant quality-of-life improvements, highlighting recent research, providing outreach opportunities, encouraging community connections, partnering with influencers, and keeping information current through digital health technologies. These methods aim to make pancreas transplantation more accessible and motivating for a diverse audience, supporting informed decision-making.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.3389/fdgth.2024.1453341.s001（source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Navigating_pancreas_transplant_perceptions_assessing_public_sentiment_and_strategies_using_AI-driven_analysis_docx/27929280）。
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务？立即联系我们获取专业方案。
