Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set-Reference-Cited by-同舟云学术

Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set

Published:2018-10-16 Issue:2 Volume:173 Page:455-463
ISSN:0167-6806
Container-title:Breast Cancer Research and Treatment
language:en
Short-container-title:Breast Cancer Res Treat

Author:

Cain Elizabeth Hope,Saha Ashirbani,Harowicz Michael R.,Marks Jeffrey R.,Marcom P. Kelly,Mazurowski Maciej A.

Funder

North Carolina Biotechnology Center

National Institutes of Health

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Oncology

Link

http://link.springer.com/article/10.1007/s10549-018-4990-9/fulltext.html

Reference46 articles.

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2. Kaufmann M, von Minckwitz G, Bear HD et al (2007) Recommendations from an international expert panel on the use of neoadjuvant (primary) systemic treatment of operable breast cancer: new perspectives 2006. Ann Oncol 18(12):1927–1934. https://doi.org/10.1093/annonc/mdm201

3. Kaufmann M, von Minckwitz G, Smith R et al (2003) International expert panel on the use of primary (preoperative) systemic treatment of operable breast cancer: review and recommendations. J Clin Oncol 21(13):2600–2608. https://doi.org/10.1200/JCO.2003.01.136

4. Heys SD, Hutcheon AW, Sarkar TK et al (2002) Neoadjuvant docetaxel in breast cancer: 3-year survival results from the Aberdeen trial. Clin Breast Cancer 3:S69–S74. https://doi.org/10.3816/CBC.2002.s.015

5. van der Hage JH, van de Velde CC, Mieog SJ (2007) Preoperative chemotherapy for women with operable breast cancer. In: Mieog SJ (ed) Cochrane database of systematic reviews. John Wiley & Sons, Ltd, Chichester. https://doi.org/10.1002/14651858.CD005002.pub2

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