Development of an absolute assignment predictor for triple-negative breast cancer subtyping using machine learning approaches-Reference-Cited by-同舟云学术

Development of an absolute assignment predictor for triple-negative breast cancer subtyping using machine learning approaches

Published:2021-02 Issue: Volume:129 Page:104171
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Ben Azzouz Fadoua^ORCID,Michel Bertrand,Lasla Hamza,Gouraud Wilfried,François Anne-Flore,Girka Fabien,Lecointre Théo,Guérin-Charbonnel Catherine,Juin Philippe P.,Campone Mario,Jézéquel Pascal

Funder

European Regional Development Fund

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

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4. Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications;Jézéquel;Breast Cancer Res.,2019

5. Challenges in projecting clustering results across gene expression-profiling datasets;Lusa;J. Natl. Cancer Inst.,2007

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