AI生成体重管理饮食计划定性评估数据表2

包含AI生成减重饮食计划的专家评估数据表,评估其与人类计划的区别及临床应用潜力。

NIAID Data Ecosystem
浏览 23
文本AIdiet planweight managementChatGPTdietary intervention
Data_Sheet_2_Qualitative evaluation of artificial intelligence-generated weight management diet plans.pdf

基本信息

模态
文本
大小
0.000130181 GB
许可
CC BY 4.0
创建/更新时间
2026-10-08
版本
v1

资源简介

AI生成体重管理饮食计划定性评估数据表2

【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 130.18 KB,主题涵盖 AI、diet plan、weight management、ChatGPT、dietary intervention,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_2_Qualitative evaluation of artificial intelligence-generated weight management diet plans.pdf》。配套论文《Artificial Intelligence Transforms the Future of Health Care》发表于 The American Journal of Medicine(2019),DOI:10.1016/j.amjmed.2019.01.017。源站首次发布:2024-03-21。

【数据内容】

源站原始描述:ImportanceThe transformative potential of artificial intelligence (AI), particularly via large language models, is increasingly being manifested in healthcare. Dietary interventions are foundational to weight management efforts, but whether AI techniques are presently capable of generating clinically applicable diet plans has not been evaluated. ObjectiveOur study sought to evaluate the potential of personalized AI-generated weight-loss diet plans for clinical applications by employing a survey-…

【数据结构与技术规格】

文件数 1 个,合计 130.18 KB。Data_Sheet_2_Qualitative evaluation of artificial intelligence-generated weight management diet plans.pdf:application/pdf,130.18 KB。数据集 DOI:10.3389/fnut.2024.1374834.s002。

【主题与分类】

源站学科分类:Animal Nutrition、Crop and Pasture Nutrition、Clinical and Sports Nutrition、Dietetics and Nutrigenomics、Nutritional Physiology、Public Nutrition Intervention。主题标签:AI、diet plan、weight management、ChatGPT、dietary intervention。

【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_2_Qualitative_evaluation_of_artificial_intelligence-generated_weight_management_diet_plans_pdf/25448434

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Kim, Dong Wook; Park, Ji Seok; Sharma, Kavita; Velazquez, Amanda; Li, Lu; Ostrominski, John W.; et al. (2024). Data_Sheet_2_Qualitative evaluation of artificial intelligence-generated weight management diet plans.pdf. Frontiers. Dataset

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从合规授权、采集治理、专业标注到数据集交付,我们提供全链路闭环服务,让高质量临床数据即拿即用。

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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。

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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)

命令行下载

curl -L -o "Data_Sheet_2_Qualitative evaluation of artificial intelligence-generated weight management diet plans.pdf" "https://ndownloader.figshare.com/files/45173653"

文件清单

  • Data_Sheet_2_Qualitative evaluation of artificial intelligence-generated weight management diet plans.pdf(130.18 KB)

文件总体积 130.18 KB(源站 API 实测)。

数据说明

ImportanceThe transformative potential of artificial intelligence (AI), particularly via large language models, is increasingly being manifested in healthcare. Dietary interventions are foundational to weight management efforts, but whether AI techniques are presently capable of generating clinically applicable diet plans has not been evaluated.
ObjectiveOur study sought to evaluate the potential of personalized AI-generated weight-loss diet plans for clinical applications by employing a survey-based assessment conducted by experts in the fields of obesity medicine and clinical nutrition.
Design, setting, and participantsWe utilized ChatGPT (4.0) to create weight-loss diet plans and selected two control diet plans from tertiary medical centers for comparison. Dietitians, physicians, and nurse practitioners specializing in obesity medicine or nutrition were invited to provide feedback on the AI-generated plans. Each plan was assessed blindly based on its effectiveness, balanced-ness, comprehensiveness, flexibility, and applicability. Personalized plans for hypothetical patients with specific health conditions were also evaluated.
Main outcomes and measuresThe primary outcomes measured included the indistinguishability of the AI diet plan from human-created plans, and the potential of personalized AI-generated diet plans for real-world clinical applications.
ResultsOf 95 participants, 67 completed the survey and were included in the final analysis. No significant differences were found among the three weight-loss diet plans in any evaluation category. Among the 14 experts who believed that they could identify the AI plan, only five did so correctly. In an evaluation involving 57 experts, the AI-generated personalized weight-loss diet plan was assessed, with scores above neutral for all evaluation variables. Several limitations, of the AI-generated plans were highlighted, including conflicting dietary considerations, lack of affordability, and insufficient specificity in recommendations, such as exact portion sizes. These limitations suggest that refining inputs could enhance the quality and applicability of AI-generated diet plans.
ConclusionDespite certain limita

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fnut.2024.1374834.s002(source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_2_Qualitative_evaluation_of_artificial_intelligence-generated_weight_management_diet_plans_pdf/25448434)。

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