Integration of artificial intelligence in the clinical management of medulloblastoma: from precision diagnosis to dynamic prognosis.
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INTRODUCTION: Medulloblastoma is the predominant malignant neuroepithelial tumor in the central nervous system among children and is recognized as one of the most aggressive tumor types. Despite advances in multimodal therapy, prognosis for certain subgroups remains poor, and survivors often face severe long-term sequelae. Artificial intelligence (AI), a field focused on enabling computers to replicate human-like intelligent behavior, is increasingly being applied to the management of challenging diseases. AREAS COVERED: In this review, the authors provide a comprehensive overview of AI applications across the entire clinical spectrum of medulloblastoma. Using articles retrieved through literature searches from PubMed and Google Scholar, through to early 2025, the authors cover AI's roles in radiological segmentation and diagnosis, noninvasive molecular subtyping, pathological analysis, tumor microenvironment characterization and prognosis prediction. The review critically appraises the current evidence level for these technologies, from proof-of-concept to clinical validation. EXPERT OPINION: AI holds immense promise for personalizing medulloblastoma care, but its clinical integration faces significant hurdles. Key challenges include the need for large, diverse datasets, robust multi-center validation, improved model interpretability, and addressing pediatric-specific ethical concerns. Future success will depend on interdisciplinary collaboration to translate these powerful tools into safe, effective, and equitable clinical practice, ultimately improving outcomes for children worldwide.