Improved Design of Bayesian Networks for Modelling Toxicity Risk in Breast Radiotherapy using Dynamic Discretization-Reference-Cited by-同舟云学术

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Improved Design of Bayesian Networks for Modelling Toxicity Risk in Breast Radiotherapy using Dynamic Discretization

Published:2022-07-18 Issue: Volume: Page:
ISSN:
Container-title:2022 International Joint Conference on Neural Networks (IJCNN)
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Author:

Ciunkiewicz Philip¹,Yanushkevich Svetlana¹,Roumeliotis Michael²,Stenhouse Kailyn¹,McGeachy Philip³,Quirk Sarah⁴,Grendarova Petra⁵

Affiliation:

1. Biometric Technologies Laboratory, University of Calgary,Calgary,AB,Canada

2. Johns Hopkins School of Medicine,Department of Radiation Oncology and Molecular Radiation Sciences,Baltimore,MD,United States

3. Tom Baker Cancer Centre,Department of Radiation Oncology,Calgary,AB,Canada

4. Harvard Medical School, Harvard University,Cambridge,MA,United States

5. Alberta Health Services,Calgary,AB,Canada

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9891857/9889787/09892531.pdf?arnumber=9892531

Reference30 articles.

1. Discretization: An Enabling Technique;liu;Data Mining and Knowledge Discovery,2002

2. Comparative analysis of discretization methods in Bayesian networks

3. Inference in hybrid Bayesian networks using dynamic discretization

4. A dynamic discretization method for reliability inference in Dynamic Bayesian Networks

5. Risk Assessment and Decision Analysis with Bayesian Networks

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1. Conditional probability table limit-based quantization for Bayesian networks: model quality, data fidelity and structure score;Applied Intelligence;2024-03

2. Decision Support Component for the Localized Epidemiological Modelling of COVID-19;2023 IEEE Symposium Series on Computational Intelligence (SSCI);2023-12-05

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