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Link to original content: https://api.crossref.org/works/10.3233/SHTI210143
{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,3,3]],"date-time":"2024-03-03T09:55:41Z","timestamp":1709459741951},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2021,5,27]],"date-time":"2021-05-27T00:00:00Z","timestamp":1622073600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,27]]},"abstract":"Ocular toxoplasmosis (OT) is commonly diagnosed through the analysis of fundus images of the eye by a specialist. Despite Deep Learning being widely used to process and recognize pathologies in medical images, the diagnosis of ocular toxoplasmosis(OT) has not yet received much attention. A predictive computational model is a valuable time-saving option if used as a support tool for the diagnosis of OT. It could also help diagnose atypical cases, being particularly useful for ophthalmologists who have less experience. In this work, we propose the use of a deep learning model to perform automatic diagnosis of ocular toxoplasmosis from images of the eye fundus. A pretrained residual neural network is fine-tuned on a dataset of samples collected at the medical center of Hospital de Cl\u00ednicas in Asunci\u00f3n, Paraguay. With sensitivity and specificity rates equal to 94% and 93%,respectively, the results show that the proposed model is highly promising. In order to replicate the results and advance further in this area of research, an open data set of images of the eye fundus labeled by ophthalmologists is made available.<\/jats:p>","DOI":"10.3233\/shti210143","type":"book-chapter","created":{"date-parts":[[2021,5,27]],"date-time":"2021-05-27T12:48:02Z","timestamp":1622119682000},"source":"Crossref","is-referenced-by-count":3,"title":["Automatic Diagnosis of Ocular Toxoplasmosis from Fundus Images with Residual Neural Networks"],"prefix":"10.3233","author":[{"given":"Rodrigo","family":"Parra","sequence":"first","affiliation":[{"name":"Universidad Americana, Asunci\u00f3n, Paraguay"}]},{"given":"Verena","family":"Ojeda","sequence":"additional","affiliation":[{"name":"Universidad Americana, Asunci\u00f3n, Paraguay"}]},{"given":"Jos\u00e9 Luis","family":"V\u00e1zquez Noguera","sequence":"additional","affiliation":[{"name":"Universidad Americana, Asunci\u00f3n, Paraguay"}]},{"given":"Miguel","family":"Garc\u00eda Torres","sequence":"additional","affiliation":[{"name":"Division of Computer Science, Universidad Pablo de Olavide, ES-41013 Seville, Spain"}]},{"given":"Julio C\u00e9sar","family":"Mello Rom\u00e1n","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias Exactas y Tecnol\u00f3gicas, Universidad Nacional de Concepci\u00f3n, Concepci\u00f3n, Paraguay"}]},{"given":"Cynthia","family":"Villalba","sequence":"additional","affiliation":[{"name":"Facultad Polit\u00e9nica, Universidad Nacional de Asunci\u00f3n, San Lorenzo, Paraguay"}]},{"given":"Jacques","family":"Facon","sequence":"additional","affiliation":[{"name":"Universidade Federal do Esp\u00edrito Santo, Brazil"}]},{"given":"Federico","family":"Divina","sequence":"additional","affiliation":[{"name":"Division of Computer Science, Universidad Pablo de Olavide, ES-41013 Seville, Spain"}]},{"given":"Olivia","family":"Cardozo","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Hospital General Pedi\u00e1trico Ni\u00f1os de Acosta \u00d1u, Paraguay"}]},{"given":"Ver\u00f3nica Elisa","family":"Castillo","sequence":"additional","affiliation":[{"name":"Departamento de Retina, C\u00e1tedra de Oftalmolog\u00eda, Hospital de Cl\u00ednicas, Facultad de Ciencias M\u00e9dicas, Universidad Nacional de Asunci\u00f3n, San Lorenzo, Paraguay"}]},{"given":"Ingrid","family":"Castro Matto","sequence":"additional","affiliation":[{"name":"Departamento de Retina, C\u00e1tedra de Oftalmolog\u00eda, Hospital de Cl\u00ednicas, Facultad de Ciencias M\u00e9dicas, Universidad Nacional de Asunci\u00f3n, San Lorenzo, Paraguay"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Public Health and Informatics"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI210143","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,25]],"date-time":"2021-10-25T13:11:08Z","timestamp":1635167468000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI210143"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,27]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti210143","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,27]]}}}