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Performance/outcomes data and physician process challenges for practical big data efforts in radiation oncology
Author(s) -
Matuszak Martha M.,
Fuller Clifton D.,
Yock Torunn I.,
Hess Clayton B.,
McNutt Todd,
Jolly Shruti,
Gabriel Peter,
Mayo Charles S.,
Thor Maria,
Caissie Amanda,
Rao Arvind,
Owen Dawn,
Smith Wade,
Palta Jatinder,
Kapoor Rishabh,
Hayman James,
Waddle Mark,
Rosenstein Barry,
Miller Robert,
Choi Seungtaek,
Moreno Amy,
Herman Joseph,
Feng Mary
Publication year - 2018
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.13136
Subject(s) - radiation oncology , big data , data science , medical physics , medicine , medical education , computer science , radiation therapy , data mining
It is an exciting time for big data efforts in radiation oncology. The use of big data to help aid both outcomes and decision‐making research is becoming a reality. However, there are true challenges that exist in the space of gathering and utilizing performance and outcomes data. Here, we summarize the current state of big data in radiation oncology with respect to outcomes and discuss some of the efforts and challenges in radiation oncology big data.