Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning

Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning

Triple negative breast cancer (TNBC) lacks well-defined molecular targets and is highly heterogenous, making treatment challenging. Using gene expression analysis, TNBC has been classified into four different subtypes: basal-like immune-activated (BLIA), basal-like immune-suppressed (BLIS), mesenchy...

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Bibliographic Details
Main Authors: Rassanee Bissanum, Sitthichok Chaichulee, Rawikant Kamolphiwong, Raphatphorn Navakanitworakul, Kanyanatt Kanokwiroon
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Journal of Personalized Medicine
Subjects:
TNBC subtype
machine learning
microarray
gene expression profile
Online Access:https://www.mdpi.com/2075-4426/11/9/881

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https://www.mdpi.com/2075-4426/11/9/881

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