9783540184027 - aime 87: european conference on artificial intelligence in medicine marseilles, august 31st – september 3rd 1987 proceedings: 33 (lecture notes in medical informatics) (18 resultados)
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Aime 87 : European Conference on Artificial Intelligence in Medicine Marseilles, August 31st ? September 3rd 1987 Proceedings
Fox, John (EDT); Fieschi, Marius (EDT); Engelbrecht, Rolf (EDT)
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Aime 87 : European Conference on Artificial Intelligence in Medicine Marseilles, August 31st ? September 3rd 1987 Proceedings
Fox, John (EDT); Fieschi, Marius (EDT); Engelbrecht, Rolf (EDT)
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Aime 87 : European Conference on Artificial Intelligence in Medicine Marseilles, August 31st ? September 3rd 1987 Proceedings
Fox, John (EDT); Fieschi, Marius (EDT); Engelbrecht, Rolf (EDT)
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Aime 87 : European Conference on Artificial Intelligence in Medicine Marseilles, August 31st ? September 3rd 1987 Proceedings
Fox, John (EDT); Fieschi, Marius (EDT); Engelbrecht, Rolf (EDT)
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AIME 87: European Conference on Artificial Intelligence in Medicine Marseilles, August 31st September 3rd 1987 Proceedings
Fox, John (Edited by)/ Fieschi, Marius (Edited by)/ Engelbrecht, Rolf (Edited by)
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Editorial: Springer Berlin Heidelberg, Springer Berlin Heidelberg, 1987
Serie: Libro 10 de 22 - Lecture Notes in Medical Informatics
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The current scarcity of expert systems where the reasoning is based on Bayesian probability theory may be due to misconceptions about probabilities found in the literature. As argued by Cheeseman (1985), these misconceptions have led to the attitud…e: 'The Bayesian approach doesn't work - so here is a new scheme'. Several of these expert systems based on ad hoc 'probability' concepts have been successful in a number of ways, demonstrating the necessity of being able to handle uncertainty in medical expert systems. They also demonstrate the need for a theoretically sound handling of uncertainty. In Andersen et al. (1986) it was postulated that knowledge organized in a causal network can be used for a unified approach to the main tasks of a medical expert system: diagnosis, planning of tests and explanations. The present paper explores this postulate in a causal probabilistic network. It also provides a practical demonstration that the problems supposedly associated with probabilistic networks are either non-existent or that practical solutions can be found. This paper reports on the methods implemented in MUNIN\* -an expert system for electromyography (EMG) (Andreassen et al. 1987). EMG is the diagnosis of muscle and nerve diseases through analysis of bioelectrical signals from muscle and nerve tissue. In Andreassen et al.
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Condición: Hervorragend. Zustand: Hervorragend | Seiten: 272 | Sprache: Englisch | Produktart: Bücher | The current scarcity of expert systems where the reasoning is based on Bayesian probability theory may be due to misconceptions about probabilities found in the literature. As argued by Cheeseman (1985), these misconceptions h…ave led to the attitude: "The Bayesian approach doesn't work - so here is a new scheme". Several of these expert systems based on ad hoc "probability" concepts have been successful in a number of ways, demonstrating the necessity of being able to handle uncertainty in medical expert systems. They also demonstrate the need for a theoretically sound handling of uncertainty. In Andersen et al. (1986) it was postulated that knowledge organized in a causal network can be used for a unified approach to the main tasks of a medical expert system: diagnosis, planning of tests and explanations. The present paper explores this postulate in a causal probabilistic network. It also provides a practical demonstration that the problems supposedly associated with probabilistic networks are either non-existent or that practical solutions can be found. This paper reports on the methods implemented in MUNIN* -an expert system for electromyography (EMG) (Andreassen et al. 1987). EMG is the diagnosis of muscle and nerve diseases through analysis of bioelectrical signals from muscle and nerve tissue. In Andreassen et al.
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Softcover. Condición: gut. 1987. AIME 87 In deutscher Sprache. pages.
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Editorial: Springer Berlin Heidelberg Aug 1987, 1987
Serie: Libro 10 de 22 - Lecture Notes in Medical Informatics
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The current scarcity of expert systems where the reasoning is based on Bayesian probability theory may be due to misconceptions about probabilities found in the literature. As argued by Cheeseman (1985), these misconceptions have le…d to the attitude: 'The Bayesian approach doesn't work - so here is a new scheme'. Several of these expert systems based on ad hoc 'probability' concepts have been successful in a number of ways, demonstrating the necessity of being able to handle uncertainty in medical expert systems. They also demonstrate the need for a theoretically sound handling of uncertainty. In Andersen et al. (1986) it was postulated that knowledge organized in a causal network can be used for a unified approach to the main tasks of a medical expert system: diagnosis, planning of tests and explanations. The present paper explores this postulate in a causal probabilistic network. It also provides a practical demonstration that the problems supposedly associated with probabilistic networks are either non-existent or that practical solutions can be found. This paper reports on the methods implemented in MUNIN\* -an expert system for electromyography (EMG) (Andreassen et al. 1987). EMG is the diagnosis of muscle and nerve diseases through analysis of bioelectrical signals from muscle and nerve tissue. In Andreassen et al. 272 pp. Englisch.
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Serie: Libro 10 de 22 - Lecture Notes in Medical Informatics
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Organized in Cooperation with IIRIAM, International Institute of Robotics and Artificial Intelligence, Marseille, FranceThe current scarcity of expert systems where the reasoning is based on Bayesian probability theor…y may be due to misconceptions about.
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Editorial: Springer-Verlag GmbH, 1987
Serie: Libro 10 de 22 - Lecture Notes in Medical Informatics
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Taschenbuch. Condición: Neu. AIME 87 | European Conference on Artificial Intelligence in Medicine Marseilles, August 31st - September 3rd 1987 Proceedings | John Fox (u. a.) | Taschenbuch | x | Englisch | 1987 | Springer-Verlag GmbH | EAN 9783540184027 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17,… 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
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Editorial: Springer Berlin Heidelberg, Springer Berlin Heidelberg Aug 1987, 1987
Serie: Libro 10 de 22 - Lecture Notes in Medical Informatics
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The current scarcity of expert systems where the reasoning is based on Bayesian probability theory may be due to misconceptions about probabilities found in the literature. As argued by Cheeseman (1985), these misconceptions have led to… the attitude: 'The Bayesian approach doesn't work - so here is a new scheme'. Several of these expert systems based on ad hoc 'probability' concepts have been successful in a number of ways, demonstrating the necessity of being able to handle uncertainty in medical expert systems. They also demonstrate the need for a theoretically sound handling of uncertainty. In Andersen et al. (1986) it was postulated that knowledge organized in a causal network can be used for a unified approach to the main tasks of a medical expert system: diagnosis, planning of tests and explanations. The present paper explores this postulate in a causal probabilistic network. It also provides a practical demonstration that the problems supposedly associated with probabilistic networks are either non-existent or that practical solutions can be found. This paper reports on the methods implemented in MUNIN\* -an expert system for electromyography (EMG) (Andreassen et al. 1987). EMG is the diagnosis of muscle and nerve diseases through analysis of bioelectrical signals from muscle and nerve tissue. In Andreassen et al.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 272 pp. Englisch.
