Oct 17, 2023 · To address this, we developed a novel Fuzzy classifier that leverages the contributions from each node's traditional deep classifier. This novel ...

ABSTRACT In the pursuit of better cancer classification, many studies have been conducted to identify the genes associated with cancer.

Oct 17, 2023 · FGS was developed using three feature selection techniques (Mutual Information, F-ClassIf, and Chi-squared) to rank genes based on their ...

In this work a novel active learning method using rough-fuzzy classifier (ALRFC) is proposed for cancer sample classification using gene expression data.

Dec 15, 2023 · The gene expression profiles generate high dimensional data, which is a major issue to deal with before creating the actual classifier. The ...

May 4, 2023 · First, a new fuzzy gene selection technique has been developed to make the datasets on gene expression less dimensional. Second, using a limited ...

Duration: 18:23
Posted: Dec 25, 2023

To identify the most significant genes associated with cancer disease, the authors [19] suggested a fuzzy gene selection approach. This approach to selecting ...

Classification of gene expression patterns using a novel type-2 fuzzy multigranulation-based SVM model for the recognition of cancer mediating biomarkers.

We propose a novel ensemble-based active learning using fuzzy-rough approach for cancer sample classification from microarray gene expression data.