Hybrid feature fusion in cervical cancer cytology: a novel dual-module approach framework for lesion detection and classification using radiomics, deep learning, and reproducibility

The proposed AI-driven cytology analysis framework offers superior lesion detection, feature fusion-based classification, and robust generalizability, providing a scalable solution for automated cervical cancer screening. Future efforts should focus on explainable AI (XAI), real-time deployment, and larger-scale validation to facilitate clinical integration.