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 ...

Statistical decision theory can be a valuable tool for policy-making decisions. In particular, environmental problems often benefit from the application of Bayesian and decision-theoretic techniques ...

Synthese, Vol. 57, No. 3, Rationality and Objectivity: Philosophical and Psychological Conceptions, Part II (Dec., 1983), pp. 341-365 (25 pages) It is argued that we need a richer version of Bayesian ...

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 ...

In my practice, I find most people involved with advanced analytics, such as predictive, data science, and ML, are familiar with the name Bayes, and can even reproduce the simple theorem below. Still, ...

Article ‘Count’ and ‘Share’ for Decision and Bayesian Computation based on listed parameters only. The articles listed below published by authors from Decision and Bayesian Computation, organized by ...

Bayesian networks, also known as Bayes nets, belief networks, or decision networks, are a powerful tool for understanding and reasoning about complex systems under uncertainty. They are essentially ...

Machine Learning to Predict Tamoxifen Nonadherence Among US Commercially Insured Patients With Metastatic Breast Cancer Ideally, specific treatment for a cancer patient is decided by a ...