Young Kwang Chae, Medical Oncologist, Co-Director of Developmental Therapeutics Lurie Cancer Center at Northwestern University, shared a post on X:
“Exciting data from Chae lab presented at AACR26!
We leveraged mRNA-derived signature to train an unbiased AI model for TLS detection in NSCLC HandE slides.
Key findings:
- AUC 0.92 (test set)
- TLS-enriched group showed significantly improved OS (HR 0.76)
Proving that HandE-based AI can provide an objective, resource-efficient way to assess TLS and predict patient outcomes.”
Other articles about Ai in Oncology on OncoDaily.