Unlocking the Potential of AI and Big Data in Cancer Research: Advances Applications

This Reprint brings together a collection of studies illustrating how artificial intelligence, machine learning, and large-scale data analytics are reshaping modern cancer research and oncology practice. The contributions span a broad spectrum of applications, including medical imaging, digital pathology, bioinformatics, clinical decision support, epidemiology, treatment optimization, and translational cancer research.A common theme across the Reprint is the growing integration of heterogeneous data sources, ranging from imaging and genomic information to electronic health records and population-level datasets, to improve cancer detection, risk stratification, prognostication, and treatment personalization. Several articles explore advanced deep learning methodologies and predictive models, while others address the practical challenges of implementing data-driven approaches in real-world clinical settings.The Reprint also highlights the increasing role of computational methods in accelerating scientific discovery, supporting precision oncology, and enabling more efficient healthcare delivery. Beyond technical innovation, the collected works emphasize reproducibility, clinical relevance, multidisciplinary collaboration, and responsible use of artificial intelligence in cancer care.