Data mining is the discovery of meaningful information or unrevealed patterns in data.
Traditional data‐mining approaches, using statistical calculations, machine learning …

Cancer is a deadly disease which requires a very complex and costly treatment. Microarray
data classification plays an important role in cancer treatment. An efficient gene selection …

Artificial neural networks (ANNs) have been utilized for classification and prediction task with
remarkable accuracy. However, its implications for unsupervised data mining using …

Clustering offers a general methodology and comes with a remarkably rich conceptual and
algorithmic framework for data analysis and data interpretation. As one of the most …

Microarray technology is an important innovation that simultaneously facilitates measuring
the expression level for thousands of genes in different samples. One basic and widely used …

Motivation One of the main challenges in applying graph convolutional neural networks
(CNNs) on gene-interaction data is the lack of understanding of the vector space to which …

The advancement of data mining technology presents a way to examine and analyse the
medical databases. Microarray data help in analysing the gene expressions, and the …

Background: Non-small cell lung cancer is defined at the molecular level by mutations and
alterations to oncogenes, including AKT1, ALK, BRAF, EGFR, HER2, KRAS, MEK1, MET …

In this paper we present two novel families of semi-supervised multi-view clustering
algorithms for relational data, providing relevance weights for views and cluster …

Background Licensed drugs may cause unexpected adverse reactions in patients, resulting
in morbidity, risk of mortality, therapy disruptions, and prolonged hospital stays. Officially …