Abstract
Immunotherapy plays a crucial role in cancer treatment, but its efficacy varies among patients, with some showing suboptimal responses. Recent studies indicate that radiotherapy not only kills tumor cells locally but also induces immunogenic cell death and modulates the tumor immune microenvironment, acting like an "in situ vaccine." This provides a strong biological basis for combining radiotherapy and immunotherapy. However, challenges remain, including individual variability in responses, complex treatment regimens, and overlapping toxicities. Artificial intelligence (AI), especially through machine learning, presents new solutions by processing high-dimensional multi-omics data. This article explores how AI enhances radiotherapy and immunotherapy combinations by optimizing synergistic effects, developing predictive biomarkers, and elucidating the regulatory mechanisms of radiotherapy on the immune microenvironment, while also discussing future directions for AI in oncology.