| Literature DB >> 30768796 |
Alan M Kalet1, Samuel M H Luk1, Mark H Phillips1.
Abstract
The recent explosion in machine learning efforts in the quality assurance (QA) space has produced a variety of proofs-of-concept many with promising results. Expected outcomes of model implementation include improvements in planning time, plan quality, advanced dosimetric QA, predictive machine maintenance, increased safety checks, and developments key for new QA paradigms driven by adaptive planning. In this article, we outline several areas of research and discuss some of the unique challenges each area presents.Keywords: artificial intelligence; machine learning; quality assurance; radiotherapy
Mesh:
Year: 2019 PMID: 30768796 DOI: 10.1002/mp.13445
Source DB: PubMed Journal: Med Phys ISSN: 0094-2405 Impact factor: 4.071