Artificial Intelligence for Diagnosis, Risk Stratification, and Prognosis of Neuroblastoma - A Systematic Review and Meta-Analysis
AI demonstrates proof-of-concept across multiple NB clinical domains.
The review synthesizes evidence on AI performance in neuroblastoma (NB) diagnosis, risk stratification, prognosis, and genomic characterization, finding that AI models match or exceed radiologist performance in differential diagnosis and outperform conventional prognostic markers descriptively, though external validation, calibration, dataset size, and pediatric-specific model development remain limiting factors.
The study highlights AI’s potential to improve neuroblastoma patient management but underscores the need for prospective validation and standardized protocols before clinical adoption.
Evidence level: Számítógépes vagy elméleti. Modellből vagy adatbányászatból származó jel.
Related signals
- Targeted immunotherapies for anaplastic lymphoma kinase-positive pediatric tumors: current advances and future perspectives
- Updates in Diagnosis, Management, and Treatment of Neuroblastoma
- Coexpression of MYCN and ALK Induces Neuroblastoma-Like Tumors From Human iPS Cell-Derived Cranial Neural Crest Cells.
- Emerging clinical and research approaches in targeted therapies for high-risk neuroblastoma
- Frequency and Clinical Significance of Clonal and Subclonal Driver Mutations in High‑Risk Neuroblastoma at Diagnosis: A Children's Oncology Group Study