| Abstrakt: |
A study conducted by researchers at Amrita Vishwa Vidyapeetham in Bengaluru, India, focuses on the early identification of cancer using gene expression data. The study addresses challenges such as high computational complexity and resource demands, as well as the presence of redundant or highly correlated selected features. The researchers propose an efficient framework based on a deep learning approach, using the Enhanced Chimp Optimization algorithm to select significant genes and the Depth-wise Separable Convolutional Neural Network to categorize cancerous and non-cancerous classes. The proposed model demonstrates a significantly higher effective performance compared to existing approaches, with an overall accuracy of 99.18%. [Extracted from the article] |
