Using LASSO regression based SVM classification to improve the predictive performance of radiation-induced pneumonitis complication in breast cancer-Reference-Cited by-同舟云学术

Using LASSO regression based SVM classification to improve the predictive performance of radiation-induced pneumonitis complication in breast cancer

Published:2018-11-17 Issue:8 Volume:41 Page:660-666
ISSN:0253-3839
Container-title:Journal of the Chinese Institute of Engineers
language:en
Short-container-title:Journal of the Chinese Institute of Engineers

Author:

Tseng Chin-Dar¹^ORCID,Shieh Chin-Shiuh¹,Huang Yu-Jie²,Chao Pei-Ju¹²,Lee Tsair-Fwu¹²³

Affiliation:

1. Medical Physics and Informatics Laboratory of Electronics Engineering, National Kaohsiung University of Science and Technology, Kaohsiung Taiwan, ROC

2. Department of Radiation Oncology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung Taiwan, ROC

3. College of Medicine, Kaohsiung Medical University, Kaohsiung Taiwan, ROC

Funder

Ministry of Science and Technology of the People's Republic of China

Ministry of Science and Technology, Taiwan

Publisher

Informa UK Limited

Subject

General Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/02533839.2018.1534616

Reference35 articles.

1. Increased Risk of Locoregional Recurrence for Women With T1-2N0 Triple-Negative Breast Cancer Treated With Modified Radical Mastectomy Without Adjuvant Radiation Therapy Compared With Breast-Conserving Therapy

2. Limited small cell lung cancer treated by combined radiotherapy and chemotherapy: evaluation of a grading system of lung fibrosis

3. Square-root lasso: pivotal recovery of sparse signals via conic programming

4. Roflumilast in symptomatic chronic obstructive pulmonary disease: two randomised clinical trials

5. A neural network model to predict lung radiation-induced pneumonitis

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