Exhaustive Exploitation of Nature-inspired Computation for Cancer Screening in an Ensemble Manner

arXiv:2404.04547v1 Announce Type: cross
Abstract: Accurate screening of cancer types is crucial for effective cancer detection and precise treatment selection. However, the association between gene expression profiles and tumors is often limited to a small number of biomarker genes. While computational methods using nature-inspired algorithms have shown promise in selecting predictive genes, existing techniques are limited by inefficient search and poor generalization across diverse datasets. This study presents a framework termed Evolutionary Optimized Diverse Ensemble Learning (EODE) to improve ensemble …

arxiv cancer cancer screening computation cs.ai cs.lg cs.ne ensemble exploitation nature screening type