scholarly journals IMRT QA using machine learning: A multi‐institutional validation

2017 ◽  
Vol 18 (5) ◽  
pp. 279-284 ◽  
Author(s):  
Gilmer Valdes ◽  
Maria F. Chan ◽  
Seng Boh Lim ◽  
Ryan Scheuermann ◽  
Joseph O. Deasy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Imrt Qa

Patient-specific IMRT QA verification using machine learning and gamma radiomics

2021 ◽  
Vol 82 ◽  
pp. 100-108
Author(s):  
Jéssica Caroline Lizar ◽  
Carolina Cariolatto Yaly ◽  
Alexandre Colello Bruno ◽  
Gustavo Arruda Viani ◽  
Juliana Fernandes Pavoni
Keyword(s):  
Machine Learning ◽  
Patient Specific ◽  
Imrt Qa

Predicting gamma passing rates for portal dosimetry‐based IMRT QA using machine learning

2019 ◽  
Vol 46 (10) ◽  
pp. 4666-4675 ◽  
Author(s):  
Dao Lam ◽  
Xizhe Zhang ◽  
Harold Li ◽  
Yang Deshan ◽  
Brayden Schott ◽  
...  
Keyword(s):  
Machine Learning ◽  
Imrt Qa ◽  
Passing Rates ◽  
Portal Dosimetry

MO-FG-202-09: Virtual IMRT QA Using Machine Learning: A Multi-Institutional Validation

2016 ◽  
Vol 43 (6Part31) ◽  
pp. 3714-3714 ◽  
Author(s):  
G Valdes ◽  
M Chan ◽  
R Scheuermann ◽  
J Deasy ◽  
T Solberg
Keyword(s):  
Machine Learning ◽  
Imrt Qa

A mathematical framework for virtual IMRT QA using machine learning

2016 ◽  
Vol 43 (7) ◽  
pp. 4323-4334 ◽  
Author(s):  
G. Valdes ◽  
R. Scheuermann ◽  
C. Y. Hung ◽  
A. Olszanski ◽  
M. Bellerive ◽  
...  
Keyword(s):  
Machine Learning ◽  
Mathematical Framework ◽  
Imrt Qa

Mind wandering as data augmentation: How mental travel supports abstraction

2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber
Keyword(s):  
Machine Learning ◽  
Data Augmentation ◽  
Mental Content ◽  
Mind Wandering ◽  
Theoretical Framework ◽  
Important Addition

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining

Mathematics for Machine Learning

2020 ◽  
Author(s):  
Marc Peter Deisenroth ◽  
A. Aldo Faisal ◽  
Cheng Soon Ong
Keyword(s):  
Machine Learning

Phase Transitions in Machine Learning

2009 ◽  
Author(s):  
Lorenza Saitta ◽  
Attilio Giordana ◽  
Antoine Cornuejols
Keyword(s):  
Machine Learning ◽  
Phase Transitions

Understanding Machine Learning

2009 ◽  
Author(s):  
Shai Shalev-Shwartz ◽  
Shai Ben-David
Keyword(s):  
Machine Learning
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