Back to Search Start Over

Using Big Data Analytics to Advance Precision Radiation Oncology.

Authors :
McNutt TR
Benedict SH
Low DA
Moore K
Shpitser I
Jiang W
Lakshminarayanan P
Cheng Z
Han P
Hui X
Nakatsugawa M
Lee J
Moore JA
Robertson SP
Shah V
Taylor R
Quon H
Wong J
DeWeese T
Source :
International journal of radiation oncology, biology, physics [Int J Radiat Oncol Biol Phys] 2018 Jun 01; Vol. 101 (2), pp. 285-291. Date of Electronic Publication: 2018 Mar 02.
Publication Year :
2018

Abstract

Big clinical data analytics as a primary component of precision medicine is discussed, identifying where these emerging tools fit in the spectrum of genomics and radiomics research. A learning health system (LHS) is conceptualized that uses clinically acquired data with machine learning to advance the initiatives of precision medicine. The LHS is comprehensive and can be used for clinical decision support, discovery, and hypothesis derivation. These developing uses can positively impact the ultimate management and therapeutic course for patients. The conceptual model for each use of clinical data, however, is different, and an overview of the implications is discussed. With advancements in technologies and culture to improve the efficiency, accuracy, and breadth of measurements of the patient condition, the concept of an LHS may be realized in precision radiation therapy.<br /> (Copyright © 2018 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1879-355X
Volume :
101
Issue :
2
Database :
MEDLINE
Journal :
International journal of radiation oncology, biology, physics
Publication Type :
Academic Journal
Accession number :
29726357
Full Text :
https://doi.org/10.1016/j.ijrobp.2018.02.028