Neuware -Medical decision support system (MDSS) are now being used in many health care institutions across the glove, these institutions have large amount of medical data stored in different format and may contain relevant data that are hidden. The use of data mining is to extract hidden knowledge from a relevant data, that is why the main aim of this book is to show how data mining methods can be applied in medical decision support system and also to design a web based expert system that can predict heart condition using neural network. The design of the system is based on VA Medical center long beach database and collected from the UCI machine learning repository. After analyzing several medical decision support systems in the relevant literature, three algorithms have been identified: multilayer perceptron, decision tree and Na�ve Bayes. These algorithms are tested under different configuration in order to find the best on the two medical dataset. Thereafter, a comparison was made with respect to their performance based on some set of performance metrics. The analysis was done using WEKA on the two medical dataset which are diabetes and heart diseases database.Books on Demand GmbH, �berseering 33, 22297 Hamburg 84 pp. Englisch.

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T�tulo: Application of data mining in medical decision support systems
Editor: LAP LAMBERT Academic Publishing Jul 2019
Fecha de publicaci�n: 2019
Idioma: Ingl�s
ISBN 10: 6139920140
ISBN 13: 9786139920143
Encuadernaci�n: Taschenbuch
Estado: Neu
Dimensiones: 220�mil�metros de ancho por 150 de alto por 6 de largo
Peso: 143 gramos

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Sinopsis

Medical decision support system (MDSS) are now being used in many health care institutions across the glove, these institutions have large amount of medical data stored in different format and may contain relevant data that are hidden. The use of data mining is to extract hidden knowledge from a relevant data, that is why the main aim of this book is to show how data mining methods can be applied in medical decision support system and also to design a web based expert system that can predict heart condition using neural network. The design of the system is based on VA Medical center long beach database and collected from the UCI machine learning repository. After analyzing several medical decision support systems in the relevant literature, three algorithms have been identified: multilayer perceptron, decision tree and Na�ve Bayes. These algorithms are tested under different configuration in order to find the best on the two medical dataset. Thereafter, a comparison was made with respect to their performance based on some set of performance metrics. The analysis was done using WEKA on the two medical dataset which are diabetes and heart diseases database.

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