{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T06:59:56Z","timestamp":1793170796577,"version":"4.5.0"},"update-to":[{"DOI":"10.1371\/journal.pntd.0010061","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T00:00:00Z","timestamp":1643155200000}}],"reference-count":113,"publisher":"Public Library of Science (PLoS)","issue":"1","license":[{"start":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T00:00:00Z","timestamp":1642032000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004916","name":"funda\u00e7\u00e3o de amparo \u00e0 pesquisa do estado do amazonas","doi-asserted-by":"publisher","award":["062.00249\/2020"],"award-info":[{"award-number":["062.00249\/2020"]}],"id":[{"id":"10.13039\/501100004916","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosntds.org"],"crossmark-restriction":false},"short-container-title":["PLoS Negl Trop Dis"],"abstract":"<jats:sec id=\"sec001\"><jats:title>Background<\/jats:title><jats:p>Neglected tropical diseases (NTDs) primarily affect the poorest populations, often living in remote, rural areas, urban slums or conflict zones. Arboviruses are a significant NTD category spread by mosquitoes. Dengue, Chikungunya, and Zika are three arboviruses that affect a large proportion of the population in Latin and South America. The clinical diagnosis of these arboviral diseases is a difficult task due to the concurrent circulation of several arboviruses which present similar symptoms, inaccurate serologic tests resulting from cross-reaction and co-infection with other arboviruses.<\/jats:p><\/jats:sec><jats:sec id=\"sec002\"><jats:title>Objective<\/jats:title><jats:p>The goal of this paper is to present evidence on the state of the art of studies investigating the automatic classification of arboviral diseases to support clinical diagnosis based on Machine Learning (ML) and Deep Learning (DL) models.<\/jats:p><\/jats:sec><jats:sec id=\"sec003\"><jats:title>Method<\/jats:title><jats:p>We carried out a Systematic Literature Review (SLR) in which Google Scholar was searched to identify key papers on the topic. From an initial 963 records (956 from string-based search and seven from a single backward snowballing procedure), only 15 relevant papers were identified.<\/jats:p><\/jats:sec><jats:sec id=\"sec004\"><jats:title>Results<\/jats:title><jats:p>Results show that current research is focused on the binary classification of Dengue, primarily using tree-based ML algorithms. Only one paper was identified using DL. Five papers presented solutions for multi-class problems, covering Dengue (and its variants) and Chikungunya. No papers were identified that investigated models to differentiate between Dengue, Chikungunya, and Zika.<\/jats:p><\/jats:sec><jats:sec id=\"sec005\"><jats:title>Conclusions<\/jats:title><jats:p>The use of an efficient clinical decision support system for arboviral diseases can improve the quality of the entire clinical process, thus increasing the accuracy of the diagnosis and the associated treatment. It should help physicians in their decision-making process and, consequently, improve the use of resources and the patient\u2019s quality of life.<\/jats:p><\/jats:sec>","DOI":"10.1371\/journal.pntd.0010061","type":"journal-article","created":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T19:33:06Z","timestamp":1642102386000},"page":"e0010061","update-policy":"https:\/\/doi.org\/10.1371\/journal.pntd.corrections_policy","source":"Crossref","is-referenced-by-count":66,"title":["Machine learning and deep learning techniques to support clinical diagnosis of arboviral diseases: A systematic review"],"prefix":"10.1371","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8109-697X","authenticated-orcid":true,"given":"Sebasti\u00e3o Rog\u00e9rio","family":"da Silva Neto","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8224-5922","authenticated-orcid":true,"given":"Thom\u00e1s","family":"Tabosa Oliveira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5334-884X","authenticated-orcid":true,"given":"Igor Vitor","family":"Teixeira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4821-8100","authenticated-orcid":true,"given":"Samuel Benjamin","family":"Aguiar de Oliveira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7307-8851","authenticated-orcid":true,"given":"Vanderson","family":"Souza Sampaio","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Theo","family":"Lynn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9163-5583","authenticated-orcid":true,"given":"Patricia Takako","family":"Endo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2022,1,13]]},"reference":[{"key":"pntd.0010061.ref001","unstructured":"World Health Organization. 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