Patricoski-Chavez et al. use a deep learning-based model with attention mechanisms that integrates clinical, mutation, and mRNA expression data from patients to predict early versus late glioma recurrence. The model outperforms traditional machine learning approaches across two independent datasets.
- Jessica A. Patricoski-Chavez
- Seema Nagpal
- Ece D. Gamsiz Uzun
