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 ...
Decision trees, influence diagrams, the value of information; Bayesian approaches, including conjugate and predictive distributions; utility theory foundations, risk preference, multiattribute utility ...
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 ...
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