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en:dydaktyka:problog:lab1 [2017/06/04 11:44] msl [Structure] |
en:dydaktyka:problog:lab1 [2019/06/27 15:49] (current) |
====== Probabilistic Programming --- Medical Cases ====== | ====== Probabilistic Programming — Diagnosis and Prediction ====== |
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This class will cover use cases of the Bayesian methods in the medical domain. First part of the class is based on article: "Local computations with probabilities on graphical structures and their application to expert systems" by Lauritzen, Steffen L. and David J. Spiegelhalter. Second part is inspired by "An intercausal cancellation model for bayesian-network engineering. International Journal of Approximate Reasoning" by S.P. Woudenberg, L. C. van der Gaag, and C. M. Rademaker. | This class will cover use cases of the Bayesian methods in the medical domain. First part of the class is based on article: "Local computations with probabilities on graphical structures and their application to expert systems" by Lauritzen, Steffen L. and David J. Spiegelhalter. Second part is inspired by "An intercausal cancellation model for bayesian-network engineering. International Journal of Approximate Reasoning" by S.P. Woudenberg, L. C. van der Gaag, and C. M. Rademaker. |
- write a corresponding Problog program: | - write a corresponding Problog program: |
* you may have to introduce additional variables for every kind of treatment to indicate if the treatment is inhibited, e.g. calcium effects in **something** that treats the osteoporosis | * you may have to introduce additional variables for every kind of treatment to indicate if the treatment is inhibited, e.g. calcium effects in **something** that treats the osteoporosis |
- what is the chance of successful treatment when we use both calcium and bisphosphonates | - what is the chance of successful treatment when we use both calcium and bisphosphonates? |