{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T19:23:36Z","timestamp":1790882616777,"version":"4.1.0"},"reference-count":50,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,11,23]],"date-time":"2022-11-23T00:00:00Z","timestamp":1669161600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"PROPESP\/UFPA","award":["008\/2017"],"award-info":[{"award-number":["008\/2017"]}]},{"name":"PROPESP\/UFPA","award":["BJT-2021\/658671"],"award-info":[{"award-number":["BJT-2021\/658671"]}]},{"name":"Funda\u00e7\u00e3o Amaz\u00f4nia Paraense de Amparo \u00e0 Pesquisa\u2014FAPESPA","award":["008\/2017"],"award-info":[{"award-number":["008\/2017"]}]},{"name":"Funda\u00e7\u00e3o Amaz\u00f4nia Paraense de Amparo \u00e0 Pesquisa\u2014FAPESPA","award":["BJT-2021\/658671"],"award-info":[{"award-number":["BJT-2021\/658671"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Emerging deep learning-based applications in precision medicine include computational histopathological analysis. However, there is a lack of the required training image datasets to generate classification and detection models. This phenomenon occurs mainly due to human factors that make it difficult to obtain well-annotated data. The present study provides a curated public collection of histopathological images (DeepHP) and a convolutional neural network model for diagnosing gastritis. Images from gastric biopsy histopathological exams were used to investigate the performance of the proposed model in detecting gastric mucosa with Helicobacter pylori infection. The DeepHP database comprises 394,926 histopathological images, of which 111 K were labeled as Helicobacter pylori positive and 283 K were Helicobacter pylori negative. We investigated the classification performance of three Convolutional Neural Network architectures. The models were tested and validated with two distinct image sets of 15% (59K patches) chosen randomly. The VGG16 architecture showed the best results with an Area Under the Curve of 0.998%. The results showed that CNN could be used to classify histopathological images from gastric mucosa with marked precision. Our model evidenced high potential and application in the computational pathology field.<\/jats:p>","DOI":"10.3390\/ijms232314581","type":"journal-article","created":{"date-parts":[[2022,11,23]],"date-time":"2022-11-23T09:50:52Z","timestamp":1669197052000},"page":"14581","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["DeepHP: A New Gastric Mucosa Histopathology Dataset for Helicobacter pylori Infection Diagnosis"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0918-1728","authenticated-orcid":false,"given":"Wanderson Gon\u00e7alves e","family":"Gon\u00e7alves","sequence":"first","affiliation":[{"name":"Laboratory of Human and Medical Genetics, Institute of Biological Sciences, Graduate Program of Genetics and Molecular Biology, Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"},{"name":"Research Center on Oncology, Graduate Program of Oncology and Medical Science, Federal University of Par\u00e1, Bel\u00e9m 66073-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2621-4897","authenticated-orcid":false,"given":"Marcelo Henrique Paula dos","family":"Santos","sequence":"additional","affiliation":[{"name":"Laboratory of Human and Medical Genetics, Institute of Biological Sciences, Graduate Program of Genetics and Molecular Biology, Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0598-5115","authenticated-orcid":false,"given":"Leonardo Miranda","family":"Brito","sequence":"additional","affiliation":[{"name":"Laboratory of Human and Medical Genetics, Institute of Biological Sciences, Graduate Program of Genetics and Molecular Biology, Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0916-6616","authenticated-orcid":false,"given":"Helber Gonzales Almeida","family":"Palheta","sequence":"additional","affiliation":[{"name":"Laboratory of Human and Medical Genetics, Institute of Biological Sciences, Graduate Program of Genetics and Molecular Biology, Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6282-0368","authenticated-orcid":false,"given":"F\u00e1bio Manoel Fran\u00e7a","family":"Lobato","sequence":"additional","affiliation":[{"name":"Laboratory of Applied Computing, Engineering and Geoscience Institute, Federal University of Western Par\u00e1, Santar\u00e9m 68040-255, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9128-3338","authenticated-orcid":false,"given":"Samia","family":"Demachki","sequence":"additional","affiliation":[{"name":"Laboratory of Human and Medical Genetics, Institute of Biological Sciences, Graduate Program of Genetics and Molecular Biology, Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7001-1483","authenticated-orcid":false,"given":"\u00c2ndrea","family":"Ribeiro-dos-Santos","sequence":"additional","affiliation":[{"name":"Laboratory of Human and Medical Genetics, Institute of Biological Sciences, Graduate Program of Genetics and Molecular Biology, Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"},{"name":"Research Center on Oncology, Graduate Program of Oncology and Medical Science, Federal University of Par\u00e1, Bel\u00e9m 66073-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9199-9419","authenticated-orcid":false,"given":"Gilderlanio Santana de","family":"Ara\u00fajo","sequence":"additional","affiliation":[{"name":"Laboratory of Human and Medical Genetics, Institute of Biological Sciences, Graduate Program of Genetics and Molecular Biology, Federal University of Par\u00e1, Bel\u00e9m 66075-110, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J. 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