研讨会程序
哮喘患者参与AI数字干预设计研讨会的程序描述，探讨患者需求、AI应用及角色转变。
基本信息
资源简介
研讨会程序
【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 5.63 KB，主题涵盖 four advisory workshops、engaging patients throughout、considering health inequities、user &# 8217、tester &# 8217，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《The workshop procedure.》。源站首次发布：2024-05-30。
【数据内容】
源站原始描述：Digital interventions with artificial intelligence (AI) can potentially support people with asthma to reduce the risk of exacerbation. Engaging patients throughout the development process is essential to ensure usability of the intervention for the end-users. Using our Connected for Asthma (C4A) intervention as an exemplar, we explore how patient involvement can shape a digital intervention. Seven Patient and Public Involvement (PPI) colleagues from the Asthma UK Centre for Applied Research part…
【数据结构与技术规格】
文件数 1 个，合计 5.63 KB。Table 1.xls：application/vnd.ms-excel，5.63 KB。数据集 DOI：10.1371/journal.pdig.0000521.t001。
【主题与分类】
源站学科分类：Genetics、Neuroscience、Biological Sciences not elsewhere classified、Information Systems not elsewhere classified、Science Policy。主题标签：four advisory workshops、engaging patients throughout、considering health inequities、user &# 8217、tester &# 8217、potentially support people、incorporated asthma monitoring、asthma whilst emphasising、asthma uk centre、asthma environmental triggers。
【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://plos.figshare.com/articles/dataset/The_workshop_procedure_/25935826
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Hui, Chi Yan; Shenton, Ann Victoria; Martin, Claire; Weatherill, David; Moylan, Dianna; Hayes, Morag; et al. (2024). The workshop procedure.. PLOS Digital Health. Dataset
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：The workshop procedure.
- DOI：10.1371/journal.pdig.0000521.t001
- 发布日期：2024-05-30
- 文件数：1 个
- 文件总体积：5.63 KB
- 源站页面：https://plos.figshare.com/articles/dataset/The_workshop_procedure_/25935826
命令行下载
curl -L -o "Table 1.xls" "https://ndownloader.figshare.com/files/46704436"
文件清单
Table 1.xls（5.63 KB）
文件总体积 5.63 KB（源站 API 实测）。
数据说明
Digital interventions with artificial intelligence (AI) can potentially support people with asthma to reduce the risk of exacerbation. Engaging patients throughout the development process is essential to ensure usability of the intervention for the end-users. Using our Connected for Asthma (C4A) intervention as an exemplar, we explore how patient involvement can shape a digital intervention. Seven Patient and Public Involvement (PPI) colleagues from the Asthma UK Centre for Applied Research participated in four advisory workshops to discuss how they would prefer to use/interact with AI to support living with their asthma, the benefit and caveats to use the AI that incorporated asthma monitoring and indoor/outdoor environmental data. Discussion focussed on the three most wanted use cases identified in our previous studies. PPI colleagues wanted AI to support data collection, remind them about self-management tasks, teach them about asthma environmental triggers, identify risk, and empower them to confidently look after their asthma whilst emphasising that AI does not replace clinicians. The discussion informed the key components in the next C4A interventions, including the approach to interacting with AI, the technology features and the research topics. Attendees highlighted the importance of considering health inequities, the presentation of data, and concerns about data accuracy, data privacy, security and ownership. We have demonstrated how patient roles can shift from that of ‘user’ (the traditional ‘tester’ of a digital intervention), to a co-design partner who shapes the next iteration of the intervention. Technology innovators should seek practical and feasible strategies to involve PPI colleagues throughout the development cycle of a digital intervention; supporting researchers to explore the barriers, concerns, enablers and advantages of implementing digital healthcare.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pdig.0000521.t001（source: https://plos.figshare.com/articles/dataset/The_workshop_procedure_/25935826）。
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。
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