Prediction of forced expiratory volume in pulmonary function test using radial basis neural networks and k-means clustering.
| Publicado en: | Journal of Medical Systems Vol. 33; no. 5; pp. 347 - 352 |
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| Autores principales: | , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Oct2009
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105327682&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105327682 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Oct2009 vid: 33 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105327682 2010441364 10.1007/s10916-008-9196-y NLM19827260 105327682 ppf: 347 ppct: 5 formats: fmt: @attributes: type: P tig: atl: Prediction of forced expiratory volume in pulmonary function test using radial basis neural networks and k-means clustering. aug: au: Manoharan SC Ramakrishnan S affil: Department of Electronics and Communication Engineering, CEG, Anna University, Chennai, India. sug: subj: Diagnosis, Computer Assisted Forced Expiratory Volume Lung Diseases Diagnosis Neural Networks (Computer) Respiratory Function Tests Methods Computer Simulation Descriptive Statistics Predictive Value of Tests Spirometry Validity Human pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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