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To predict this disease, a pilot scale study was carried out in 30 villages of Karimnagar district of Telangana from 2004 to 2007 to collect epidemiological and socio-economic data. The collected data are analysed by employing various machine learning techniques such as Na\u00efve Bayes (NB), logistic model tree, probabilistic neural network, J48 (C4.5), classification and regression tree, JRip and gradient boosting machine. The performances of these algorithms are reported using sensitivity, specificity, accuracy and area under ROC curve (AUC). Among all employed classification methods, NB yielded the best AUC of 64% and was equally statistically significant with the rest of the classifiers. Similarly, the J48 algorithm generated 23 decision rules that help in developing an early warning system to implement better prevention and control efforts in the management of filariasis.<\/jats:p>","DOI":"10.1017\/s0950268819001481","type":"journal-article","created":{"date-parts":[[2019,9,2]],"date-time":"2019-09-02T11:47:24Z","timestamp":1567424844000},"source":"Crossref","is-referenced-by-count":33,"title":["Applications of machine learning techniques to predict filariasis using socio-economic factors"],"prefix":"10.1017","volume":"147","author":[{"given":"Phani Krishna","family":"Kondeti","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kumar","family":"Ravi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3263-3905","authenticated-orcid":false,"given":"Srinivasa Rao","family":"Mutheneni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Madhusudhan Rao","family":"Kadiri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sriram","family":"Kumaraswamy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ravi","family":"Vadlamani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suryanaryana Murty","family":"Upadhyayula","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2019,9,2]]},"reference":[{"key":"S0950268819001481_ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.parepi.2016.11.001"},{"key":"S0950268819001481_ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.apgeog.2011.06.011"},{"key":"S0950268819001481_ref37","doi-asserted-by":"publisher","DOI":"10.1016\/B978-1-55860-377-6.50023-2"},{"key":"S0950268819001481_ref38","volume-title":"Classification and Regression Trees","author":"Breiman","year":"1984"},{"key":"S0950268819001481_ref34","unstructured":"John GH and Langley P (1995) Estimating continuous distributions in Bayesian classifiers. 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