CALM - Dynamic, Explainable Risk Scoring for Smoldering Multiple Myeloma Progression Using an Attention-Based Deep Survival Model

Learn about CALM, an innovative attention-based deep survival model designed to provide dynamic and explainable risk scoring for predicting smoldering multiple myeloma progression in this 15-minute mathematical oncology presentation. Discover how this cutting-edge predictive modeling approach combines deep learning techniques with survival analysis to create interpretable risk assessments for patients with smoldering multiple myeloma, a precancerous condition that can progress to active multiple myeloma. Explore the model's attention mechanisms that enable both accurate predictions and clear explanations of the factors driving risk scores, making it valuable for clinical decision-making. Gain insights into how mathematical oncology approaches can transform cancer risk prediction by providing healthcare professionals with tools that are both powerful and transparent, ultimately supporting better patient care and treatment planning decisions.