{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T05:58:32Z","timestamp":1790834312433,"version":"4.1.0"},"reference-count":36,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2023,12,18]],"date-time":"2023-12-18T00:00:00Z","timestamp":1702857600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Nasopharyngeal carcinoma (NPC) is an epithelial cancer originating in the nasopharynx epithelium. Nevertheless, annotating pathology slides remains a bottleneck in the development of AI-driven pathology models and applications. In the present study, we aim to demonstrate the feasibility of using immunohistochemistry (IHC) for annotation by non-pathologists and to develop an efficient model for distinguishing NPC without the time-consuming involvement of pathologists. For this study, we gathered NPC slides from 251 different patients, comprising hematoxylin and eosin (H&amp;E) slides, pan-cytokeratin (Pan-CK) IHC slides, and Epstein\u2013Barr virus-encoded small RNA (EBER) slides. The annotation of NPC regions in the H&amp;E slides was carried out by a non-pathologist trainee who had access to corresponding Pan-CK IHC slides, both with and without EBER slides. The training process utilized ResNeXt, a deep neural network featuring a residual and inception architecture. In the validation set, NPC exhibited an AUC of 0.896, with a sensitivity of 0.919 and a specificity of 0.878. This study represents a significant breakthrough: the successful application of deep convolutional neural networks to identify NPC without the need for expert pathologist annotations. Our results underscore the potential of laboratory techniques to substantially reduce the workload of pathologists.<\/jats:p>","DOI":"10.3390\/diagnostics13243685","type":"journal-article","created":{"date-parts":[[2023,12,18]],"date-time":"2023-12-18T08:55:29Z","timestamp":1702889729000},"page":"3685","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Immunohistochemical Stain-Aided Annotation Accelerates Machine Learning and Deep Learning Model Development in the Pathologic Diagnosis of Nasopharyngeal Carcinoma"],"prefix":"10.3390","volume":"13","author":[{"given":"Tai-Pei","family":"Lin","sequence":"first","affiliation":[{"name":"Department of Life Sciences, National Chung Hsing University, Taichung 402, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7130-1781","authenticated-orcid":false,"given":"Chiou-Ying","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Molecular Biology, National Chung Hsing University, Taichung 402, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ko-Jiunn","family":"Liu","sequence":"additional","affiliation":[{"name":"National Institute of Cancer Research, National Health Research Institutes, Tainan 704, Taiwan"},{"name":"Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan"},{"name":"Institute of Clinical Pharmacy and Pharmaceutical Sciences and Institute of Clinical Medicine, National Cheng Kung University, Tainan 701, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3696-4827","authenticated-orcid":false,"given":"Meng-Yuan","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Life Sciences, National Chung Hsing University, Taichung 402, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6381-4269","authenticated-orcid":false,"given":"Yen-Lin","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1012","DOI":"10.1016\/S0140-6736(15)00055-0","article-title":"Nasopharyngeal carcinoma","volume":"387","author":"Chua","year":"2016","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"394","DOI":"10.3322\/caac.21492","article-title":"Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"68","author":"Bray","year":"2018","journal-title":"CA Cancer J. 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