Enhanced Directed Random Walk for the Identification of Breast Cancer Prognostic Markers from Multiclass Expression Data

Enhanced Directed Random Walk for the Identification of Breast Cancer Prognostic Markers from Multiclass Expression Data

Artificial intelligence in healthcare can potentially identify the probability of contracting a particular disease more accurately. There are five common molecular subtypes of breast cancer: luminal A, luminal B, basal, ERBB2, and normal-like. Previous investigations showed that pathway-based microa...

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Bibliographic Details
Main Authors: Hui Wen Nies, Mohd Saberi Mohamad, Zalmiyah Zakaria, Weng Howe Chan, Muhammad Akmal Remli, Yong Hui Nies
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Entropy
Subjects:
prognostic markers
breast cancer
multiclass
microarray analysis
ANOVA
pathway selection
Online Access:https://www.mdpi.com/1099-4300/23/9/1232

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