Detecting Cancer Genes Using Graph Neural Networks

Authors

• Marvin Masabo Nkaka, St. Mary's University

Files

Contributor

Ramirez, Ricardo (Faculty Mentor)

Digital Publisher

Digital Commons at St. Mary's University

Publication Date

Spring 2026

Keywords

Cancer, Neural Networks, Detection, Medical technology

Description

• Cancer survival prediction is challenging due to the complexity of genomic data and limited samples especially for rarer cancer types. • To address this challenge, we developed an Artificial Neural Network (ANN) model for survival analysis using RNA-sequencing gene expression data from The Cancer Genome Atlas (TCGA). • Moreover, a key concept we investigate was how transfer learning enhanced our model’s performance especially for rarer cancer types difficult to perform accurate survival analysis due to their limited samples.

Format

pdf

Size

1 poster

City

San Antonio, Texas

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.