Shalini Saha

Navigating AI and machine learning in cancer research: an end-to-end translational framework

This review provides a comprehensive pipeline for artificial intelligence/machine learning in cancer research, including preclinical research, clinical decision support, and real-world implementation, and critically examines multi-omics fusion architectures, regularization-based machine learning, batch-effect harmonization, explainable AI, and federated learning.