Machine Learning-Driven Discovery of Quadruple-Negative Breast Cancer Subtypes from Gene Expression Data.
Bikram SahooNikita JinnaPadmashree RidaZandra PinnixAlex ZelikovskyPublished in: ISBRA (1) (2024)
Keyphrases
- breast cancer
- gene expression data
- machine learning
- analysis of gene expression data
- microarray
- cancer datasets
- feature selection
- gene expression
- logistic regression
- early detection
- gene expression analysis
- high dimensionality
- microarray data
- gene expression profiles
- gene regulatory networks
- data sets
- cancer diagnosis
- decision trees
- knowledge discovery
- microarray datasets
- high dimensional
- gene networks
- natural language processing
- learning algorithm
- gene selection
- computer vision
- cancer classification
- data mining
- gene expression datasets
- machine learning methods
- pattern recognition
- genomic data
- data analysis
- high throughput
- high dimensional data
- information extraction
- support vector machine
- statistical methods
- gene ontology
- text categorization
- dimensionality reduction
- text mining
- nearest neighbor