IIS: Workshop on Population Health Data Measurement, Representation, and Predictive Modeling.

IIS：人口健康数据测量、表示和预测建模研讨会。

• 批准号: 1146740
• 负责人: Bruce Schatz
• 金额: $ 8.75万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1146740&HistoricalAwards=false
• 关键词: IIS; Workshop; Population; Health; Data

The workshop brings together a group of scientists with complementary expertise in health informatics, population health, and computer science to identify the research challenges and opportunities in population health data measurement, representation, and predictive modeling. Despite great advances in measurement, computing, and communication technologies, the health data measurement relies on legacy practices (e.g., phone surveys). In contrast, billions of persons worldwide have mobile devices, such as cell phones and music players, which contain measurement sensors and are increasingly network aware. If these devices could be appropriately employed for population health data measurement, they could revolutionize the acquisition and use of population health data. However, there are many research challenges that need to be addressed in order to make widespread use of actionable population health data. The workshop is organized around a vision of actionable data for population health. It covers a broad range of questions such as: What data should be recorded to measure everyday health? How should this data be most helpfully collected? How should the sensor data be classified into actionable data? How should the diverse sources be judged for quality? How should this data be mined and correlated? How can population data be transformed into usable knowledge? How should this data be used to develop practical health systems? How can multiple knowledge sources be integrated for multiple users? How can existing data (medical records and clinical trials) be leveraged using model-based inference to support customized decision making and refine predictive models? What is the impact of this new data on health quality and cost? Workshop participants include experts in the areas of health informatics, knowledge representation and inference, machine learning and data mining. Thw workshop aims to increase the awareness of research challenges and opportunities in health informatics in general, and population data measurement, representation, and predictive modeling in particular, among researchers in data mining, knowledge representation and inference, machine learning, text analysis, human-computer interaction, social networks and social media, semantic web, decision theory. It also aims to make researchers in health informatics, public health, and related areas better aware of the state of the art informatics approaches that could be leveraged to develop the next generation health informatics infrastructure. The workshop results, including new research challenges and opportunities in discovery informatics, will be broadly disseminated through the workshop report, publications by workshop participants, and outreach efforts through follow-up activities that engage the research community.

研讨会汇集了一群在健康信息学、人口健康和计算机科学方面具有互补专业知识的科学家，以确定人口健康数据测量、表示和预测建模方面的研究挑战和机会。尽管在测量、计算和通信技术方面取得了巨大进步，但健康数据测量依赖于传统做法(例如，电话调查)。相比之下，全球有数十亿人拥有移动设备，如手机和音乐播放器，这些设备包含测量传感器，并越来越具有网络意识。如果这些设备能够适当地用于人口健康数据测量，它们可能会彻底改变人口健康数据的获取和使用。然而，有许多研究挑战需要解决，以便广泛使用可操作的人口健康数据。研讨会是围绕人口健康的可操作数据的愿景而组织的。它涵盖了广泛的问题，例如：应该记录哪些数据来衡量日常健康状况？如何收集这些数据才是最有帮助的？应如何将传感器数据分类为可操作的数据？应该如何判断不同来源的质量？应该如何挖掘和关联这些数据？如何将人口数据转化为有用的知识？应该如何利用这些数据来开发实用的卫生系统？如何为多个用户集成多个知识源？如何使用基于模型的推理来利用现有数据(医疗记录和临床试验)来支持定制决策和改进预测模型？这一新数据对健康质量和成本有何影响？研讨会参与者包括卫生信息学、知识表示和推理、机器学习和数据挖掘领域的专家。该讲习班旨在提高数据挖掘、知识表示和推理、机器学习、文本分析、人机交互、社交网络和社交媒体、语义网、决策理论等领域的研究人员对卫生信息学的研究挑战和机遇的认识，特别是对人口数据测量、表示和预测建模的认识。它还旨在使健康信息学、公共卫生和相关领域的研究人员更好地了解可用于开发下一代健康信息学基础设施的最先进的信息学方法。讲习班成果，包括发现信息学方面的新的研究挑战和机会，将通过讲习班报告、讲习班参与者的出版物以及通过与研究界参与的后续活动进行的外联努力来广泛传播。