AI RESEARCH
Learning from Limited and Incomplete Data: A Multimodal Framework for Predicting Pathological Response in NSCLC
arXiv CS.CV
•
ArXi:2603.15100v1 Announce Type: new Major pathological response (pR) following neoadjuvant therapy is a clinically meaningful endpoint in non-small cell lung cancer, strongly associated with improved survival. However, accurate preoperative prediction of pR remains challenging, particularly in real-world clinical settings characterized by limited data availability and incomplete clinical profiles.