Cancer Subtype

Cancer subtype classification aims to identify distinct groups of cancers based on their molecular and morphological characteristics, improving diagnosis and treatment personalization. Current research heavily utilizes machine learning, employing various architectures like transformers, graph neural networks, and gradient-boosted models to analyze multi-omics data (genomic, proteomic, etc.) and histopathological images (H&E stained slides and WSIs). These methods are being refined to address challenges like data imbalance and computational cost, often incorporating techniques such as multi-instance learning and ensemble methods to enhance accuracy and robustness. Improved subtype classification holds significant promise for advancing precision oncology by enabling more targeted therapies and better patient stratification.