Machine learning for prediction of chemoradiation therapy response in rectal cancer using pre-treatment and mid-radiation multi-parametric MRI-Reference-Cited by-同舟云学术

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Machine learning for prediction of chemoradiation therapy response in rectal cancer using pre-treatment and mid-radiation multi-parametric MRI

Published:2019-09 Issue: Volume:61 Page:33-40
ISSN:0730-725X
Container-title:Magnetic Resonance Imaging
language:en
Short-container-title:Magnetic Resonance Imaging

Author:

Shi Liming,Zhang Yang,Nie Ke,Sun Xiaonan,Niu Tianye,Yue Ning,Kwong Tiffany,Chang Peter,Chow Daniel,Chen Jeon-Hor,Su Min-Ying

Funder

NIH

Rutgers Cancer Institute of New Jersey

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Basic Public Welfare Research Program of Zhejiang Province

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,Biomedical Engineering,Biophysics

Reference40 articles.

1. Long-term outcome in patients with a pathological complete response after chemoradiation for rectal cancer: a pooled analysis of individual patient data;Maas;Lancet Oncol,2010

2. Chemoradiotherapy for rectal cancer: an updated analysis of factors affecting pathological response;Sanghera;Clin Oncol,2008

3. Patterns of failure and survival for nonoperative treatment of stage c0 distal rectal cancer following neoadjuvant chemoradiation therapy;Habr-Gama;J Gastrointest Surg,2006

4. Neoadjuvant chemoradiation and local excision for T2-3 rectal cancer;Borschitz;Ann Surg Oncol,2008

5. Watch-and-wait approach versus surgical resection after chemoradiotherapy for patients with rectal cancer (the OnCoRe project): a propensity-score matched cohort analysis;Renehan;Lancet Oncol,2016

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