Improving Cancer Diagnosis with Hybrid Neural Networks: A Comprehensive Narrative Review

Hybrid neural network applications for cancer diagnosis mark a substantial development in medical science. The creation, integration, and potential of hybrid neural networks across different cancer types are rigorously analyzed in this paper. This review attempts to provide a thorough understanding of their function in early detection and customized management of cancer by analyzing their adaptability and efficacy, independent of imaging modalities. The review provides insights into potential future avenues for utilizing hybrid neural networks to improve the results of cancer treatment through this investigation.