作者
Akash P Kansagra, J Yu John-Paul, Arindam R Chatterjee, Leon Lenchik, Daniel S Chow, Adam B Prater, Jean Yeh, Ankur M Doshi, C Matthew Hawkins, Marta E Heilbrun, Stacy E Smith, Martin Oselkin, Pushpender Gupta, Sayed Ali
发表日期
2016/1/1
来源
Academic radiology
卷号
23
期号
1
页码范围
30-42
出版商
Elsevier
简介
Rapid growth in the amount of data that is electronically recorded as part of routine clinical operations has generated great interest in the use of Big Data methodologies to address clinical and research questions. These methods can efficiently analyze and deliver insights from high-volume, high-variety, and high-growth rate datasets generated across the continuum of care, thereby forgoing the time, cost, and effort of more focused and controlled hypothesis-driven research. By virtue of an existing robust information technology infrastructure and years of archived digital data, radiology departments are particularly well positioned to take advantage of emerging Big Data techniques. In this review, we describe four areas in which Big Data is poised to have an immediate impact on radiology practice, research, and operations. In addition, we provide an overview of the Big Data adoption cycle and describe how academic …
引用总数
20162017201820192020202120222023202471516201276101
学术搜索中的文章
AP Kansagra, JY John-Paul, AR Chatterjee, L Lenchik… - Academic radiology, 2016