Artificial intelligence-based morphologic classification and molecular characterization of neuroblastic tumors from digital histopathology - Siddhi Ramesh; Emma Dyer; Monica Pomaville; Kristina Doytcheva; James Dolezal; Sara Kochanny; Rachel Terhaar; Casey J. Mehrhoff; Kritika Patel; Jacob Brewer; Benjamin Kusswurm; Arlene Naranjo; et al. (npj Precision Oncology)
Abstract A deep learning model using attention-based multiple instance learning (aMIL) and self-supervised learning (SSL) was developed to perform pathologic classification of neuroblastic tumors and assess MYCN-amplification status using H&E-stained whole slide images from the largest reported cohort to date. The model showed promising performance in identifying diagnostic category, grade, mitosis-karyorrhexis index (MKI), and MYCN-amplification with validation on an external test dataset, suggesting potential for AI-assisted neuroblastoma classification.