Ideally, specific treatment for a cancer patient is decided by a multidisciplinary tumor board, integrating prior clinical experience, published data, and patient-specific factors to develop a ...
This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...
Lakkaraju, Himabindu, and Jure Leskovec. "Confusions over Time: An Interpretable Bayesian Model to Characterize Trends in Decision Making." Advances in Neural Information Processing Systems (NeurIPS) ...
Show More 1 Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer & Research Institute, Tampa, FL Ideally, specific treatment for a cancer patient is decided by a multidisciplinary ...
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