Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A model for reasoning about persistence and causation
Computational Intelligence
Dynamic network models for forecasting
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
A computational scheme for reasoning in dynamic probabilistic networks
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Sensor validation using dynamic belief networks
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Multiple perspective dynamic decision making
Artificial Intelligence
Dynamic Network Construction and Updating Techniques for the Diagnosis of Acute Abdominal Pain
IEEE Transactions on Pattern Analysis and Machine Intelligence
The probabilistic program dependence graph and its application to fault diagnosis
ISSTA '08 Proceedings of the 2008 international symposium on Software testing and analysis
Editorial: Bayesian networks in biomedicine and health-care
Artificial Intelligence in Medicine
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Cancer spread is a non-deterministic dynamic process. As a consequence, the design of an assistant system for the diagnosis and prognosis of the extent of a cancer should be based on a representation method which deals with both uncertainty and time. The ultimate goal is to know the stage of development reached by a cancer in the patient, previously to selecting the appropriate treatment. A network of probabilistic events in discrete time (NPEDT) is a type of temporal Bayesian network that permits to model the causal mechanisms associated with the time evolution of a process. The present work describes NasoNet, a system which applies the formalism of NPEDTs to the case of nasopharyngeal cancer. We have made use of temporal noisy gates to model the dynamic causal interactions that take place in the domain. The methodology we describe is sufficiently general to be applied to any other type of cancer.