Big Data and Comparative Effectiveness Research in Radiation Oncology: Synergy and Accelerated Discovery

Abstract

Several advances in large data set collection and processing have the potential to provide a wave of new insights and improvements in the use of radiation therapy for cancer treatment. The era of electronic health records, genomics, and improving information technology resources creates the opportunity to leverage these developments to create a learning healthcare system that can rapidly deliver informative clinical evidence. By merging concepts from comparative effectiveness research with the tools and analytic approaches of "big data," it is hoped that this union will accelerate discovery, improve evidence for decision making, and increase the availability of highly relevant, personalized information. This combination offers the potential to provide data and analysis that can be leveraged for ultra-personalized medicine and high-quality, cutting-edge radiation therapy.

DOI: 10.3389/fonc.2015.00274

Extracted Key Phrases

02000400020162017
Citations per Year

1,337 Citations

Semantic Scholar estimates that this publication has 1,337 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Trifiletti2015BigDA, title={Big Data and Comparative Effectiveness Research in Radiation Oncology: Synergy and Accelerated Discovery}, author={Daniel M. Trifiletti and Timothy N. Showalter}, journal={Frontiers in oncology}, year={2015}, volume={5}, pages={274} }