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Título:
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Feature Selection, Ranking of Each Feature and Classification for the Diagnosis of Community Acquired Legionella Pneumonia
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Autor/a:
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Monte-Moreno, Enric; Solé-Casals, Jordi; Fiz Fernández, José Antonio; Sopena Galindo, Nieves
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Otros autores:
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Universitat de Vic. Escola Politècnica Superior; Universitat de Vic. Grup de Recerca en Tecnologies Digitals; International Work-Conference on Artificial and Natural Networks (6è : 2001: Granada); IWANN 2001 |
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Notas:
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Diagnosis of community acquired legionella pneumonia (CALP) is currently performed by means of laboratory techniques which may delay diagnosis several hours. To determine whether ANN can categorize CALP and non-legionella community-acquired pneumonia (NLCAP) and be standard for use by clinicians, we prospectively studied 203 patients with community-acquired pneumonia (CAP) diagnosed by laboratory tests. Twenty one clinical and analytical variables were recorded to train a neural net with two classes (LCAP or NLCAP class). In this paper we deal with the problem of diagnosis, feature selection, and ranking of the features as a function of their classification importance, and the design of a classifier the criteria of maximizing the ROC (Receiving operating characteristics) area, which gives a good trade-off between true positives and false negatives. In order to guarantee the validity of the statistics; the train-validation-test databases were rotated by the jackknife technique, and a multistarting procedure was done in order to make the system insensitive to local maxima. |
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Materia(s):
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-Legionel·la pneumophila |
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Derechos:
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(c) Springer (The original publication is available at www.springerlink.com)
Tots els drets reservats
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Tipo de documento:
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Objeto de conferencia |
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Editor:
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Springer
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