Premenopausal breast cancer: potential clinical utility of a multi-omics based machine learning approach for patient stratification-Reference-Cited by-同舟云学术

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Premenopausal breast cancer: potential clinical utility of a multi-omics based machine learning approach for patient stratification

Published:2018-04-11 Issue:2 Volume:9 Page:175-186
ISSN:1878-5077
Container-title:EPMA Journal
language:en
Short-container-title:EPMA Journal

Author:

Fröhlich Holger,Patjoshi Sabyasachi,Yeghiazaryan Kristina,Kehrer Christina,Kuhn Walther,Golubnitschaja Olga

Publisher

Springer Science and Business Media LLC

Subject

Biochemistry (medical),Health Policy,Drug Discovery

Link

http://link.springer.com/article/10.1007/s13167-018-0131-0/fulltext.html

Reference45 articles.

1. Golubnitschaja O, Debald M, Yeghiazaryan K, Kuhn W, Pešta M, Costigliola V, et al. Breast cancer epidemic in the early 21st century: evaluation of risk factors, cumulative questionnaires and recommendations for preventive measures. Tumor Biol. 2016;37(10):12941–57. https://doi.org/10.1007/s13277-016-5168-x .

2. Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61(2):69–90.

3. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66(1):7–30.

4. Smokovski I, Risteski M, Polivka J Jr, Zubor P, Konieczka K, Costigliola V, et al. Postmenopausal breast cancer: European challenge and innovative concepts. EPMA J. 2017;8(2):159–69. https://doi.org/10.1007/s13167-017-0094-6 .

5. American Cancer Society. Global cancer facts & figures. 2nd ed. Atlanta: American Cancer Society; 2011.

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