dc.contributor |
Universitat de Vic. Escola Politècnica Superior |
dc.contributor |
Universitat de Vic. Grup de Recerca en Tecnologies Digitals |
dc.contributor |
International Work-Conference on Artificial and Natural Networks (6è : 2001: Granada) |
dc.contributor |
IWANN 2001 |
dc.contributor.author |
Monte-Moreno, Enric |
dc.contributor.author |
Solé-Casals, Jordi |
dc.contributor.author |
Fiz Fernández, José Antonio |
dc.contributor.author |
Sopena Galindo, Nieves |
dc.date |
2001 |
dc.identifier |
E. Monte, J. Solé-Casals, J.A. Fiz, N. Sopena “Feature Selection, Ranking of Each Feature and Classification for the Diagnosis of Community Acquired Legionella Pneumonia“,Bio-Inspired Applications of Connectionism, Proceedings of 6th International Work-Conference on Artificial and Natural Networks, IWANN 2001, Series: LNCS, Vol. 2084, Mira, Jose; Prieto, Alberto (Eds.) 2001, XXVII, ISBN: 3-540-42235-8 |
dc.identifier |
3-540-42235-8 |
dc.identifier |
0302-9743 |
dc.identifier |
http://hdl.handle.net/10854/3013 |
dc.identifier |
https://doi.org/10.1007/3-540-45723-2_43 |
dc.identifier.uri |
http://hdl.handle.net/10854/3013 |
dc.description |
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. |
dc.format |
application/pdf |
dc.language |
eng |
dc.publisher |
Springer |
dc.relation |
http://link.springer.com/chapter/10.1007%2F3-540-45723-2_43 |
dc.rights |
(c) Springer (The original publication is available at www.springerlink.com) |
dc.rights |
Tots els drets reservats |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.subject |
Legionel·la pneumophila |
dc.title |
Feature Selection, Ranking of Each Feature and Classification for the Diagnosis of Community Acquired Legionella Pneumonia |
dc.type |
info:eu-repo/semantics/conferenceObject |