2 papers
eess.IV2026
Uncertainty-driven training for three-dimensional calibrated lung nodule classification
Giuseppe Tripodi, Alessandro De Rosis, Saleh Rezaeiravesh
In this work, we present an uncertainty-driven training framework for three-dimensional computed tomography (CT) lung nodule classification, where validation-based uncertainty esti…
cs.LG2026
Probing, Fusion, and Trustworthiness: A Systematic Evaluation of Foundation Model Representations for Multimodal Cancer Analysis
Jingyu Hu, Giuseppe Tripodi, Reed Naidoo +2
Foundation models (FMs) have emerged as powerful representation extractors for medical data, yet their generalizability to datasets under distribution shift remains underexplored.…