“Advancing Normal Tissue Complication Probability Modeling with Supervised Contrastive Learning for Predicting Osteoradionecrosis” by a multidisciplinary team led by Prof. Canahuate at the University of Iowa and including UIC CS Prof. Zhang and Prof. Marai has received a Best Paper Award at the ACM Symposium on Applied Computing (SAC) 2026 in Thessaloniki, Greece. The paper describes the development of a supervised contrastive learning model for predicting a delayed-onset, significant toxicity associated with radiation therapy treatment for head and neck cancer.

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