241 citations · 266 across the 4 of their papers we have counts for
4 papers
Interpretable Graph Kolmogorov-Arnold Networks for Multi-Cancer Classification and Biomarker Identification using Multi-Omics Data
Fadi Alharbi, Nishant Budhiraja, Aleksandar Vakanski +4
The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational models in precision cancer diagnost…
Comparative Analysis of Multi-Omics Integration Using Advanced Graph Neural Networks for Cancer Classification
Fadi Alharbi, Aleksandar Vakanski, Boyu Zhang +2
Multi-omics data is increasingly being utilized to advance computational methods for cancer classification. However, multi-omics data integration poses significant challenges due t…
LASSO-MOGAT: A Multi-Omics Graph Attention Framework for Cancer Classification
Fadi Alharbi, Aleksandar Vakanski, Murtada K. Elbashir +1
The application of machine learning methods to analyze changes in gene expression patterns has recently emerged as a powerful approach in cancer research, enhancing our understandi…
Machine Learning Methods for Cancer Classification Using Gene Expression Data: A Review
Fadi Alharbi, Aleksandar Vakanski
Cancer is a term that denotes a group of diseases caused by abnormal growth of cells that can spread in different parts of the body. According to the World Health Organization (WHO…