{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T17:23:42Z","timestamp":1776187422810,"version":"3.50.1"},"reference-count":17,"publisher":"Wiley","license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010785","name":"Universidad Ju\u00e1rez Aut\u00f3noma de Tabasco","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010785","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003141","name":"Consejo Nacional de Ciencia y Tecnolog\u00eda","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003141","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p><jats:italic>Background<\/jats:italic>. Guillain-Barr\u00e9 Syndrome (GBS) is a potentially fatal autoimmune neurological disorder. The severity varies among the four main subtypes, named as Acute Inflammatory Demyelinating Polyneuropathy (AIDP), Acute Motor Axonal Neuropathy (AMAN), Acute Motor Sensory Axonal Neuropathy (AMSAN), and Miller-Fisher Syndrome (MF). A proper subtype identification may help to promptly carry out adequate treatment in patients.<jats:italic> Method<\/jats:italic>. We perform experiments with 15 single classifiers in two scenarios: four subtypes\u2019 classification and One versus All (OvA) classification. We used a dataset with the 16 relevant features identified in a previous phase. Performance evaluation is made by 10-fold cross validation (10-FCV). Typical classification performance measures are used. A statistical test is conducted in order to identify the top five classifiers for each case.<jats:italic> Results<\/jats:italic>. In four GBS subtypes\u2019 classification, half of the classifiers investigated in this study obtained an average accuracy above 0.90. In OvA classification, the two subtypes with the largest number of instances resulted in the best classification results.<jats:italic> Conclusions<\/jats:italic>. This study represents a comprehensive effort on creating a predictive model for Guillain-Barr\u00e9 Syndrome subtypes. Also, the analysis performed in this work provides insight about the best single classifiers for each classification case.<\/jats:p>","DOI":"10.1155\/2017\/8424198","type":"journal-article","created":{"date-parts":[[2017,4,11]],"date-time":"2017-04-11T17:02:31Z","timestamp":1491930151000},"page":"1-9","source":"Crossref","is-referenced-by-count":9,"title":["A Predictive Model for Guillain-Barr\u00e9 Syndrome Based on Single Learning Algorithms"],"prefix":"10.1155","volume":"2017","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1893-1332","authenticated-orcid":true,"given":"Juana","family":"Canul-Reich","sequence":"first","affiliation":[{"name":"Divisi\u00f3n Acad\u00e9mica de Inform\u00e1tica y Sistemas, Universidad Ju\u00e1rez Aut\u00f3noma de Tabasco, Km. 1 Carretera Cunduac\u00e1n, Jalpa de M\u00e9ndez, Col. Esmeralda, CP 86690, Cunduac\u00e1n, TAB, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Frausto-Sol\u00eds","sequence":"additional","affiliation":[{"name":"Instituto Tecnol\u00f3gico de Ciudad Madero, Av. 1o. de Mayo esq. Sor Juana In\u00e9s de la Cruz s\/n, Col. Los Mangos, 89440 Ciudad Madero, TAMPS, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3146-9349","authenticated-orcid":true,"given":"Jos\u00e9","family":"Hern\u00e1ndez-Torruco","sequence":"additional","affiliation":[{"name":"Divisi\u00f3n Acad\u00e9mica de Inform\u00e1tica y Sistemas, Universidad Ju\u00e1rez Aut\u00f3noma de Tabasco, Km. 1 Carretera Cunduac\u00e1n, Jalpa de M\u00e9ndez, Col. 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