Artificial intelligence in cervical cancer immunology: A review of mechanisms and clinical applications

Cervical cancer (CC) remains a significant global health burden, with its pathogenesis closely linked to persistent high-risk human papillomavirus (HPV) infection and immune evasion mechanisms. In recent years, artificial intelligence (AI) has emerged as a transformative force in oncology, particularly in immunology research, offering novel insights into disease mechanisms and enhancing clinical decision-making. This review systematically summarizes the latest advances in AI-driven research and applications in CC immunology. By integrating multi-omics data, AI enables high-resolution profiling of the tumor immune microenvironment and facilitates the identification of key biomarkers and signaling pathways. In clinical settings, AI has significantly improved the accuracy and efficiency of CC screening, diagnosis, treatment optimization, and prognosis prediction. Despite persistent challenges such as data heterogeneity, model interpretability, and the need for prospective validation, the convergence of AI and immunology is paving the way for more precise and personalized management of CC. This review underscores the translational potential of AI in immunology and highlights its role in advancing the global effort to eliminate CC.