利用数字双胞胎来创建代表卵巢癌患者及其家人的人物
Youjia Wang1, Khushboo Thaker2, Vivian Hui3
1School of Nursing, University of Pittsburgh, PA, USA.
Studies in health technology and informatics
|July 25, 2024
概括
这项研究创建了数字双胞胎,代表卵巢癌 (OvCa) 患者和护理人员,以应对在线寻求健康信息的挑战. 当真实用户数据稀缺时,这些人物有助于开发AI模型.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 卵巢癌 (OvCa) 患者和护理人员难以获得可靠的在线健康信息.
- 现有的推系统可能缺乏细微的用户理解,以提供个性化的支持.
研究的目的:
- 描述OvCa患者和护理人员创建数字双胞胎的方法.
- 在研究背景下展示这些数字双胞胎的实用性.
- 为了应对AI模型开发中有限的用户数据的挑战.
主要方法:
- 数字双胞胎是通过整合来自在线癌症论坛的数据,患者/护理人员采访,专家意见和临床笔记来开发的.
- 三角化方法确保了全面和现实的人物表现.
- 为OvCa患者和护理人员生成了十个不同的人物,反映了不同的癌症旅程和信息需求.
主要成果:
- 为OvCa患者和护理人员成功创建了10个数字双胞胎人格.
- 对于这些人来说,在应对信息搜索挑战时,已经证明了使用案例.
- 建立了一种用于人工智能培训生成代表性用户数据的方法.
结论:
- 数字双胞胎在AI模型开发的早期阶段为克服数据短缺提供了可行的解决方案.
- 这些人物可以加强人工智能系统的培训,从而产生更有效的健康信息推工具.
- HELPeR系统的数字双胞胎方法为瘤学中用户需求建模提供了一种新的方式.
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