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Journal article

Applications and limitations of machine learning in radiation oncology

Abstract:

Machine learning approaches to problem-solving are growing rapidly within healthcare, and radiation oncology is no exception. With the burgeoning interest in machine learning comes the significant risk of misaligned expectations as to what it can and cannot accomplish. This paper evaluates the role of machine learning and the problems it solves within the context of current clinical challenges in radiation oncology. The role of learning algorithms within the workflow for external beam radiati...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1259/bjr.20190001

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
St Catherine's College
Role:
Author
ORCID:
0000-0003-3371-5929
Publisher:
British Institute of Radiology
Journal:
British Journal of Radiology More from this journal
Volume:
92
Issue:
1100
Article number:
20190001
Publication date:
2019-05-21
Acceptance date:
2019-05-16
DOI:
EISSN:
1748-880X
ISSN:
0007-1285
Keywords:
Pubs id:
pubs:999085
UUID:
uuid:abc977ef-6ccd-4cc1-adca-ccbaa1cbadb6
Local pid:
pubs:999085
Source identifiers:
999085
Deposit date:
2019-05-17

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