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Title: WE-H-BRB-01: Overview of the ASTRO-NIH-AAPM 2015 Workshop On Exploring Opportunities for Radiation Oncology in the Era of Big Data

Abstract

Big Data in Radiation Oncology: (1) Overview of the NIH 2015 Big Data Workshop, (2) Where do we stand in the applications of big data in radiation oncology?, and (3) Learning Health Systems for Radiation Oncology: Needs and Challenges for Future Success The overriding goal of this trio panel of presentations is to improve awareness of the wide ranging opportunities for big data impact on patient quality care and enhancing potential for research and collaboration opportunities with NIH and a host of new big data initiatives. This presentation will also summarize the Big Data workshop that was held at the NIH Campus on August 13–14, 2015 and sponsored by AAPM, ASTRO, and NIH. The workshop included discussion of current Big Data cancer registry initiatives, safety and incident reporting systems, and other strategies that will have the greatest impact on radiation oncology research, quality assurance, safety, and outcomes analysis. Learning Objectives: To discuss current and future sources of big data for use in radiation oncology research To optimize our current data collection by adopting new strategies from outside radiation oncology To determine what new knowledge big data can provide for clinical decision support for personalized medicine L. Xing, NIH/NCI Google Inc.

Authors:
 [1]
  1. University of California Davis Medical Center (United States)
Publication Date:
OSTI Identifier:
22679144
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; DRUGS; HOST; LEARNING; NEOPLASMS; PATIENTS; POTENTIALS; QUALITY ASSURANCE; RADIOTHERAPY; SAFETY; QUALITY MANAGEMENT

Citation Formats

Benedict, S. WE-H-BRB-01: Overview of the ASTRO-NIH-AAPM 2015 Workshop On Exploring Opportunities for Radiation Oncology in the Era of Big Data. United States: N. p., 2016. Web. doi:10.1118/1.4957989.
Benedict, S. WE-H-BRB-01: Overview of the ASTRO-NIH-AAPM 2015 Workshop On Exploring Opportunities for Radiation Oncology in the Era of Big Data. United States. doi:10.1118/1.4957989.
Benedict, S. Wed . "WE-H-BRB-01: Overview of the ASTRO-NIH-AAPM 2015 Workshop On Exploring Opportunities for Radiation Oncology in the Era of Big Data". United States. doi:10.1118/1.4957989.
@article{osti_22679144,
title = {WE-H-BRB-01: Overview of the ASTRO-NIH-AAPM 2015 Workshop On Exploring Opportunities for Radiation Oncology in the Era of Big Data},
author = {Benedict, S.},
abstractNote = {Big Data in Radiation Oncology: (1) Overview of the NIH 2015 Big Data Workshop, (2) Where do we stand in the applications of big data in radiation oncology?, and (3) Learning Health Systems for Radiation Oncology: Needs and Challenges for Future Success The overriding goal of this trio panel of presentations is to improve awareness of the wide ranging opportunities for big data impact on patient quality care and enhancing potential for research and collaboration opportunities with NIH and a host of new big data initiatives. This presentation will also summarize the Big Data workshop that was held at the NIH Campus on August 13–14, 2015 and sponsored by AAPM, ASTRO, and NIH. The workshop included discussion of current Big Data cancer registry initiatives, safety and incident reporting systems, and other strategies that will have the greatest impact on radiation oncology research, quality assurance, safety, and outcomes analysis. Learning Objectives: To discuss current and future sources of big data for use in radiation oncology research To optimize our current data collection by adopting new strategies from outside radiation oncology To determine what new knowledge big data can provide for clinical decision support for personalized medicine L. Xing, NIH/NCI Google Inc.},
doi = {10.1118/1.4957989},
journal = {Medical Physics},
issn = {0094-2405},
number = 6,
volume = 43,
place = {United States},
year = {2016},
month = {6}
}