Research Information System
in: Advances in Immunology, Academic Press , 2026
This chapter reviews AI-driven approaches, including machine learning and deep learning, for analyzing microbiome data in head and neck cancer (HNC). It highlights the role of artificial intelligence in identifying microbial biomarkers, predicting treatment outcomes, and supporting early diagnosis through the integration of multi-omics and clinical data. The chapter also discusses key challenges, including data heterogeneity, model interpretability, and clinical applicability, and outlines future directions for precision oncology. Recent advances in artificial intelligence have enabled novel analytical strategies for microbiome-based research in HNC, offering new opportunities for biomarker discovery and data-driven clinical decision-making. By combining high-dimensional microbiome profiles with clinical and multi-omics information, AI-based methods provide a promising framework for improving disease characterization and advancing precision oncology.