Y. Peng and J.A. Reggia "Plausability of diagnostic hypothesis", in Proceedings (AAAI-86), Philadelphia, 1986, pp. 140145.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....networks and its extension by conditioning and clustering, and his stochastic simulation proposal [9] researchers have investigated various approaches, especially in the context of medical diagnosis. Our work on greedy algorithms can be viewed as an extension of the line of work presented in [10], 11] ranging from two layered networks to general belief networks. More recently, best first search algorithms were proposed [17] as well as algorithms based on linear programming [15] Various other authors have worked on extending some of these algorithms to the task of finding the k ....

Peng, Y., Reggia, J. A., 1986. Plausability of Diagnostic Hypothesis, In Proc. of AAAI-86.

....the most likely disease a patient is suffering from. In decoding, the task is to identify the most likely input message which was transmitted over a noisy channel, given the observed output. Researchers have investigated various approaches to finding the mpe in a belief network. See, e.g. [35, 9, 36, 37]) Recent proposals include best first search algorithms [48] and algorithms based on linear programming [41] The problem is to find x 0 such that P (x 0 ) max x P (x; e) max x Pi i P (x i ; ejx pa i ) where x = x 1 ; xn ) and e is a set of observations, on subsets of the ....

Y. Peng and J.A. Reggia. Plausability of diagnostic hypothesis. In National Conference on Artificial Intelligence (AAAI86), pages 140--145, 1986.

....only if the network is sparse enough to allow small cutsets or small clusters. Following Pearl s stochastic simulation algorithms for the MPE task [ Pearl, 1988 ] the suitability of Stochastic Local Search (SLS) algorithms for MPE was studied in the context of Medical diagnosis applications [ Peng and Reggia, 1986 ] Peng and Reggia, 1989 ] and more recently in [ Kask and Dechter, 1999b ] Best first search algorithms were also proposed [ Shimony and Charniak, 1991 ] as well as algorithms based on linear programming [ Santos, 1991 ] 2 Background 2.1 Notation and definitions Belief Networks provide ....

Y. Peng and J.A. Reggia. Plausability of diagnostic hypothesis. In National Conference on Artificial Intelligence (AAAI86), pages 140--145, 1986.

....This task appears in applications such as diagnosis and abduction. For example, it can suggest the disease from which a patient suffers given data on clinical findings. Researchers have investigated various approaches to finding the mpe in a belief network. See, e.g. Pearl, 1988; Cooper, 1984; Peng and Reggia, 1986; Peng and Reggia, 1989) Recent proposals include best first search algorithms (Shimony and Charniack, 1991) and algorithms based on linear programming (Santos, 1991) The problem is to find x 0 such that P (x 0 ) max x Pi i P (x i ; ejx pa i ) where x = x 1 ; x n ) and e is a set ....

Y. Peng and J.A. Reggia. Plausability of diagnostic hypothesis. In National Conference on Artificial Intelligence (AAAI86), pages 140--145, 1986.

No context found.

Y. Peng and J.A. Reggia "Plausability of diagnostic hypothesis", in Proceedings (AAAI-86), Philadelphia, 1986, pp. 140145.

No context found.

Y. Peng and J.A. Reggia. Plausability of diagnostic hypothesis. In National Conference on Artificial Intelligence (AAAI86), pages 140--145, 1986.

No context found.

Y. Peng and J.A. Reggia. Plausability of diagnostic hypothesis. In National Conference on Artificial Intelligence (AAAI'86), pages 140--145, 1986.

No context found.

Y. Peng and J.A. Reggia "Plausability of diagnostic hypothesis", in Proceedings (AAAI-86), Philadelphia, 1986, pp. 140145.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC