Suppr超能文献

计算健康科学的理由。

The Case for Computational Health Science.

作者信息

Barnes M, Hanson C, Giraud-Carrier C

机构信息

1Department of Public Health, Brigham Young University, Provo, UT 84602 USA.

2Department of Computer Science, Brigham Young University, Provo, UT 84602 USA.

出版信息

J Healthc Inform Res. 2018;2(1):99-110. doi: 10.1007/s41666-018-0024-y. Epub 2018 May 30.

Abstract

In this introductory paper, we begin by making the case for Computational Health Science, which we define as the interdisciplinary efforts of health scientists, computer scientists, engineers, psychologists, and other social scientists, to conduct innovative research that will inform future practice directed at changing health behavior through improved communication, networking, and social capital. We recognize and discuss some of the main challenges involved with such an enterprise, but also highlight the associated benefits, which, we argue, significantly outweigh them. We then provide a brief summary of the contributions to this first Special Issue on Computational Health Science.

摘要

在这篇引言性论文中,我们首先阐述计算健康科学的理由。我们将计算健康科学定义为健康科学家、计算机科学家、工程师、心理学家以及其他社会科学家的跨学科努力,旨在开展创新性研究,为未来通过改善沟通、网络和社会资本来改变健康行为的实践提供指导。我们认识并讨论了这项事业所涉及的一些主要挑战,但也强调了相关的益处,我们认为这些益处远远超过挑战。然后,我们简要总结了对关于计算健康科学的这第一期特刊的贡献。

相似文献

1
The Case for Computational Health Science.计算健康科学的理由。
J Healthc Inform Res. 2018;2(1):99-110. doi: 10.1007/s41666-018-0024-y. Epub 2018 May 30.
5
Future Perfect? The Future of the Social Sciences in Public Health.将来完成时?公共卫生领域社会科学的未来。
Front Public Health. 2018 Jan 10;5:357. doi: 10.3389/fpubh.2017.00357. eCollection 2017.
8
Preface.前言。
Math Biosci Eng. 2016 Jun 1;13(3):i. doi: 10.3934/mbe.201600i.

本文引用的文献

5
From Big Data to Knowledge in the Social Sciences.从大数据到社会科学中的知识
Ann Am Acad Pol Soc Sci. 2015 May 1;659(1):16-32. doi: 10.1177/0002716215570007.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验