{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:20:09Z","timestamp":1772907609010,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T00:00:00Z","timestamp":1640131200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"ILIND\u2014Instituto Lus\u00f3fono de Investiga\u00e7\u00e3o e Desenvolvimento","award":["COFAC\/ILIND\/COPELABS\/1\/2020"],"award-info":[{"award-number":["COFAC\/ILIND\/COPELABS\/1\/2020"]}]},{"name":"ILIND\u2014Instituto Lus\u00f3fono de Investiga\u00e7\u00e3o e Desenvolvimento","award":["COFAC\/ILIND\/COPELABS\/3\/2020"],"award-info":[{"award-number":["COFAC\/ILIND\/COPELABS\/3\/2020"]}]},{"name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior, Brasil (CAPES)","award":["Finance Code 001"],"award-info":[{"award-number":["Finance Code 001"]}]},{"name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Santa Catarina (FAPESC)","award":["EDITAL DE CHAMADA P\u00daBLICA FAPESC No.  06\/2017"],"award-info":[{"award-number":["EDITAL DE CHAMADA P\u00daBLICA FAPESC No.  06\/2017"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>The health sector faces a series of problems generated by patients who miss their scheduled appointments. The main challenge to this problem is to understand the patient\u2019s profile and predict potential absences. The goal of this work is to explore the main causes that contribute to a patient\u2019s no-show and develop a prediction model able to identify whether the patient will attend their scheduled appointment or not. The study was based on data from clinics that serve the Unified Health System (SUS) at the University of Vale do Itaja\u00ed in southern Brazil. The model obtained was tested on a real collected dataset with about 5000 samples. The best model result was performed by the Random Forest classifier. It had the best Recall Rate (0.91) and achieved an ROC curve rate of 0.969. This research was approved and authorized by the Ethics Committee of the University of Vale do Itaja\u00ed, under opinion 4270,234, contemplating the General Data Protection Law.<\/jats:p>","DOI":"10.3390\/fi14010003","type":"journal-article","created":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T10:24:52Z","timestamp":1640168692000},"page":"3","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Application of Machine Learning Techniques to Predict a Patient\u2019s No-Show in the Healthcare Sector"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5842-8451","authenticated-orcid":false,"given":"Luiz Henrique A.","family":"Salazar","sequence":"first","affiliation":[{"name":"Laboratory of Embedded and Distributed Systems, University of Vale do Itajai, Itajai 88302-901, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0446-9271","authenticated-orcid":false,"given":"Valderi R. Q.","family":"Leithardt","sequence":"additional","affiliation":[{"name":"VALORIZA, Research Center for Endogenous Resources Valorization, Instituto Polit\u00e9cnico de Portalegre, 7300-555 Portalegre, Portugal"},{"name":"COPELABS, Universidade Lus\u00f3fona de Humanidades e Tecnologias, 1749-024 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1896-0520","authenticated-orcid":false,"given":"Wemerson Delcio","family":"Parreira","sequence":"additional","affiliation":[{"name":"Laboratory of Embedded and Distributed Systems, University of Vale do Itajai, Itajai 88302-901, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2986-5353","authenticated-orcid":false,"given":"Anita M.","family":"da Rocha Fernandes","sequence":"additional","affiliation":[{"name":"Laboratory of Embedded and Distributed Systems, University of Vale do Itajai, Itajai 88302-901, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0358-2056","authenticated-orcid":false,"given":"Jorge Luis Vict\u00f3ria","family":"Barbosa","sequence":"additional","affiliation":[{"name":"Applied Computing Graduate Program, University of Vale do Rio dos Sinos, Av. Unisinos 950, Bairro Cristo Rei, Sao Leopoldo 93022-750, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1111-3513","authenticated-orcid":false,"given":"S\u00e9rgio Duarte","family":"Correia","sequence":"additional","affiliation":[{"name":"VALORIZA, Research Center for Endogenous Resources Valorization, Instituto Polit\u00e9cnico de Portalegre, 7300-555 Portalegre, Portugal"},{"name":"COPELABS, Universidade Lus\u00f3fona de Humanidades e Tecnologias, 1749-024 Lisbon, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Kheirkhah, P., Feng, Q., Travis, L.M., Tavakoli-Tabasi, S., and Sharafkhaneh, A. (2016). Prevalence, predictors and economic consequences of no-shows. BMC Health Serv. Res., 16.","DOI":"10.1186\/s12913-015-1243-z"},{"key":"ref_2","unstructured":"(2021, November 25). 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