Machine learning identifies immune-perinatal predictors of infantile hemangioma

This study presents a robust, interpretable machine learning model that leverages immune-perinatal features to predict IH risk. Our findings support the notion that IH may serve as a paradigm for inflammation-associated vascular tumorigenesis, with implications for early detection and personalized intervention strategies in immune-driven neoplasms.