{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T06:07:44Z","timestamp":1791612464650,"version":"4.3.4"},"reference-count":37,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2012,10,15]],"date-time":"2012-10-15T00:00:00Z","timestamp":1350259200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["The Laryngoscope"],"published-print":{"date-parts":[[2012,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objective:<\/jats:title><jats:p>Laryngeal function can be evaluated from multiple perspectives, including aerodynamic input, acoustic output, and mucosal wave vibratory characteristics. To determine the classifying power of each of these, we used a multilayer perceptron artificial neural network (ANN) to classify data as normal, glottic insufficiency, or tension asymmetry.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study design:<\/jats:title><jats:p>Case series analyzing data obtained from excised larynges simulating different conditions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods:<\/jats:title><jats:p>Aerodynamic, acoustic, and videokymographic data were collected from excised canine larynges simulating normal, glottic insufficiency, and tension asymmetry. Classification of samples was performed using a multilayer perceptron ANN.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results:<\/jats:title><jats:p>A classification accuracy of 84% was achieved when including all parameters. Classification accuracy dropped below 75% when using only aerodynamic or acoustic parameters and below 65% when using only videokymographic parameters.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions:<\/jats:title><jats:p>Samples were classified with the greatest accuracy when using a wide range of parameters. Decreased classification accuracies for individual groups of parameters demonstrate the importance of a comprehensive voice assessment when evaluating dysphonia. Laryngoscope, 2012<\/jats:p><\/jats:sec>","DOI":"10.1002\/lary.23549","type":"journal-article","created":{"date-parts":[[2012,10,15]],"date-time":"2012-10-15T18:16:31Z","timestamp":1350324991000},"page":"2773-2780","source":"Crossref","is-referenced-by-count":9,"title":["Classification of glottic insufficiency and tension asymmetry using a multilayer perceptron"],"prefix":"10.1002","volume":"122","author":[{"given":"Matthew R.","family":"Hoffman","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ketan","family":"Surender","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erin E.","family":"Devine","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jack J.","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2012,10,15]]},"reference":[{"key":"e_1_2_7_2_2","doi-asserted-by":"publisher","DOI":"10.3109\/14015430903582128"},{"key":"e_1_2_7_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0892-1997(01)00053-4"},{"key":"e_1_2_7_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvoice.2005.04.007"},{"key":"e_1_2_7_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvoice.2006.09.010"},{"key":"e_1_2_7_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00405-002-0542-2"},{"key":"e_1_2_7_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0892-1997(97)80026-4"},{"key":"e_1_2_7_8_2","first-page":"247","article-title":"Reliability and clinical relevance of perceptual evaluation of pathological voices","volume":"119","author":"Dejonckere PH","year":"1998","journal-title":"Rev Laryngol Otol Rhinol (Bord)"},{"key":"e_1_2_7_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvoice.2010.02.001"},{"key":"e_1_2_7_10_2","doi-asserted-by":"publisher","DOI":"10.1177\/000348940811700603"},{"key":"e_1_2_7_11_2","first-page":"1","volume-title":"Workshop on Acoustic Voice Analysis: Summary Statement","author":"Titze IR","year":"1995"},{"key":"e_1_2_7_12_2","doi-asserted-by":"publisher","DOI":"10.1159\/000316140"},{"key":"e_1_2_7_13_2","first-page":"298","volume-title":"Clinical Measurement of Speech and Voice","author":"Baken RJ","year":"2000"},{"key":"e_1_2_7_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(95)91746-2"},{"key":"e_1_2_7_15_2","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198538493.001.0001","volume-title":"Neural networks for Pattern Recognition","author":"Bishop CM","year":"1995"},{"key":"e_1_2_7_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2005.07.022"},{"key":"e_1_2_7_17_2","doi-asserted-by":"publisher","DOI":"10.1038\/323533a0"},{"key":"e_1_2_7_18_2","first-page":"40","article-title":"Feature selection using a multilayer perceptron","volume":"2","author":"Ruck DW","year":"1990","journal-title":"J Neural Network Comp"},{"key":"e_1_2_7_19_2","doi-asserted-by":"publisher","DOI":"10.1288\/00005537-199308000-00008"},{"key":"e_1_2_7_20_2","doi-asserted-by":"publisher","DOI":"10.1177\/000348949810700602"},{"key":"e_1_2_7_21_2","doi-asserted-by":"publisher","DOI":"10.1177\/000348940711600210"},{"key":"e_1_2_7_22_2","unstructured":"DaelemansW HosteV.Evaluation of machine learning methods for natural language processing tasks. 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