Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breas...
Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breast cancer
About this item
Full title
Author / Creator
Chen, Yuli , Li, Haojia , Janowczyk, Andrew , Toro, Paula , Corredor, Germán , Whitney, Jon , Lu, Cheng , Koyuncu, Can F. , Mokhtari, Mojgan , Buzzy, Christina , Ganesan, Shridar , Feldman, Michael D. , Fu, Pingfu , Corbin, Haley , Harbhajanka, Aparna , Gilmore, Hannah , Goldstein, Lori J. , Davidson, Nancy E. , Desai, Sangeeta , Parmar, Vani and Madabhushi, Anant
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
Prognostic markers currently utilized in clinical practice for estrogen receptor-positive (ER+) and lymph node-negative (LN−) invasive breast cancer (IBC) patients include the Nottingham grading system and Oncotype Dx (ODx). However, these biomarkers are not always optimal and remain subject to inter-/intra-observer variability and high cost. In th...
Alternative Titles
Full title
Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breast cancer
Authors, Artists and Contributors
Author / Creator
Li, Haojia
Janowczyk, Andrew
Toro, Paula
Corredor, Germán
Whitney, Jon
Lu, Cheng
Koyuncu, Can F.
Mokhtari, Mojgan
Buzzy, Christina
Ganesan, Shridar
Feldman, Michael D.
Fu, Pingfu
Corbin, Haley
Harbhajanka, Aparna
Gilmore, Hannah
Goldstein, Lori J.
Davidson, Nancy E.
Desai, Sangeeta
Parmar, Vani
Madabhushi, Anant
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_67dd37d216ad4551903031aedcfbd8d7
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_67dd37d216ad4551903031aedcfbd8d7
Other Identifiers
ISSN
2374-4677
E-ISSN
2374-4677
DOI
10.1038/s41523-023-00545-y
