{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T15:18:04Z","timestamp":1790263084508,"version":"4.1.0"},"reference-count":30,"publisher":"Canadian Science Publishing","issue":"6","license":[{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.nrcresearchpress.com\/page\/about\/CorporateTextAndDataMining"}],"funder":[{"name":"Ministerio de Ciencia, Tecnolog\u00eda e Innovaci\u00f3n","award":["907-2021"],"award-info":[{"award-number":["907-2021"]}]},{"name":"Universidad Aut\u00f3noma de Manizales","award":["674-102"],"award-info":[{"award-number":["674-102"]}]}],"content-domain":{"domain":["cdnsciencepub.com"],"crossmark-restriction":false},"short-container-title":["Biochem. Cell Biol."],"published-print":{"date-parts":[[2023,12,1]]},"abstract":"<jats:p> Here, a machine learning tool (YOLOv5) enables the detection of Cryptosporidium microorganisms using optical and phase contrast microscope images. The two databases were processed using 520 images (optical microscopy) and 1200 images (phase contrast microscopy). It used Python libraries to label, standardize the size, and crop the images to generate the input tensors to the YOLOv5 network (s, m, and l). It implemented two experiments using randomly initialized weights in optical and phase contrast microscope images. The other two experiments used the parameters for the best training time obtained before and after retraining the models. Metrics used to assess model accuracy were mean average accuracy, confusion matrix, and the F1 scores. All three metrics confirmed that the optimal model used the best epoch of optical imaging training and retraining with phase contrast imaging. Experiments with randomly initialized weights with optical imaging showed the lowest precision for Cryptosporidium detection. The most stable model was YOLOv5m, with the best results in all categories. However, the differences between all models are lower than 2%, and YOLOv5s is the best option for Cryptosporidium detection considering the differences in computational costs of the models. <\/jats:p>","DOI":"10.1139\/bcb-2023-0059","type":"journal-article","created":{"date-parts":[[2023,8,16]],"date-time":"2023-08-16T21:37:40Z","timestamp":1692221860000},"page":"538-549","update-policy":"https:\/\/doi.org\/10.1139\/csp-crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Automatic detection of <i>Cryptosporidium<\/i> in optical microscopy images using YOLOv5<i>x<\/i>: a comparative study"],"prefix":"10.1139","volume":"101","author":[{"given":"Johan Sebastian Lopez","family":"Salguero","sequence":"first","affiliation":[{"name":"Departamento de F\u00edsica y Matem\u00e1ticas, Universidad Aut\u00f3noma de Manizales, Antigua Estaci\u00f3n del Ferrocarril","place":["Manizales, Colombia"]},{"name":"Departamento de Ciencias B\u00e1sicas, Universidad Aut\u00f3noma de Manizales, Antigua Estaci\u00f3n del Ferrocarril","place":["Manizales, Colombia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melissa Rodr\u00edguez","family":"Rend\u00f3n","sequence":"additional","affiliation":[{"name":"Departamento de F\u00edsica y Matem\u00e1ticas, Universidad Aut\u00f3noma de Manizales, Antigua Estaci\u00f3n del Ferrocarril","place":["Manizales, Colombia"]},{"name":"Departamento de Ciencias B\u00e1sicas, Universidad Aut\u00f3noma de Manizales, Antigua Estaci\u00f3n del Ferrocarril","place":["Manizales, Colombia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica Trivi\u00f1o","family":"Valencia","sequence":"additional","affiliation":[{"name":"Departamento de Ciencias B\u00e1sicas, Universidad Aut\u00f3noma de Manizales, Antigua Estaci\u00f3n del Ferrocarril","place":["Manizales, Colombia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jorge Andr\u00e9s Cuellar","family":"Gil","sequence":"additional","affiliation":[{"name":"Departamento de Ciencias B\u00e1sicas, Universidad Aut\u00f3noma de Manizales, Antigua Estaci\u00f3n del Ferrocarril","place":["Manizales, Colombia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlos Andr\u00e9s Naranjo","family":"Galvis","sequence":"additional","affiliation":[{"name":"Departamento de Ciencias B\u00e1sicas, Universidad Aut\u00f3noma de Manizales, Antigua Estaci\u00f3n del Ferrocarril","place":["Manizales, Colombia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oscar Moscoso","family":"Londo\u00f1o","sequence":"additional","affiliation":[{"name":"Departamento de F\u00edsica y Matem\u00e1ticas, Universidad Aut\u00f3noma de Manizales, Antigua Estaci\u00f3n del Ferrocarril","place":["Manizales, Colombia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1141-3276","authenticated-orcid":false,"given":"C\u00e9sar Leandro Londo\u00f1o","family":"Calder\u00f3n","sequence":"additional","affiliation":[{"name":"Departamento de F\u00edsica y Matem\u00e1ticas, Universidad Aut\u00f3noma de Manizales, Antigua Estaci\u00f3n del Ferrocarril","place":["Manizales, Colombia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabio Augusto Gonz\u00e1les","family":"Osorio","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda de Sistemas e Industrial","place":["Bogot\u00e1, Colombia"]},{"name":"Universidad Nacional de Colombia","place":["Bogot\u00e1, Colombia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reinel Tabares","family":"Soto","sequence":"additional","affiliation":[{"name":"Departamento de Electr\u00f3nica y Automatizaci\u00f3n Industrial","place":["Manizales, Colombia"]},{"name":"Universidad Aut\u00f3noma de Manizales, Antigua Estaci\u00f3n del Ferrocarril","place":["Manizales, Colombia"]},{"name":"Departamento de Sistemas e Inform\u00e1tica","place":["Caldas, Colombia"]},{"name":"Universidad de Caldas","place":["Caldas, Colombia"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"155","reference":[{"key":"refg1\/ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mlwa.2021.100138"},{"key":"refg2\/ref2","doi-asserted-by":"publisher","DOI":"10.14745\/ccdr.v46i06a07"},{"key":"refg3\/ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.imed.2022.08.004"},{"key":"refg4\/ref4","doi-asserted-by":"publisher","DOI":"10.18494\/SAM.2020.3130"},{"key":"refg5\/ref5","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1610.02357"},{"key":"refg6\/ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"refg7\/ref7","doi-asserted-by":"publisher","DOI":"10.1007\/s40475-018-0149-3"},{"key":"refg8\/ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"refg9\/ref9","doi-asserted-by":"publisher","DOI":"10.2166\/wst.2020.515"},{"key":"refg10\/ref10","first-page":"770","volume-title":"Proc. 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