{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T12:46:49Z","timestamp":1792414009004,"version":"4.4.0"},"reference-count":0,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T00:00:00Z","timestamp":1792368000000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Automated cytology screening is essential for early cervical cancer prevention, where gigapixel whole-slide images (WSIs) are typically partitioned into tiles for tile-level feature extraction and subsequent WSI-level diagnosis aggregation. However, existing tile-level methods remain constrained by limited input sizes, which frequently obscures sparse and morphologically subtle abnormal cells. Furthermore, these methods commonly formulate tile-level representation learning as a coarse single-label classification task, thereby failing to capture the complex co-occurrence patterns and morphological heterogeneity of cervical cytological abnormalities.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We propose the Frequency-Aware Multi-Label Learning Network (FMCerNet), a tile-level feature extractor equipped with a Large-Field Frequency-Enhanced ViT (LFreq-ViT) backbone and a Coarse-to-Fine multi-label classification (C2F) head. The former incorporates a Dual-Tree Complex Wavelet Transform module to efficiently extract frequency-domain features from large-scale tiles, whereas the latter enhances fine-grained tile representation decoding through hierarchical supervision. Experiments on both public and private datasets demonstrate that FMCerNet improves the accuracy of positive screening and fine-grained subtype classification while maintaining high inference speed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and Implementation<\/jats:title>\n                    <jats:p>Code at https:\/\/github.com\/imAzhou\/FMCerNet and archived on Zenodo (doi:10.5281\/zenodo.22886105).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary Information<\/jats:title>\n                    <jats:p>Supplementary files are available with the manuscript.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag759","type":"journal-article","created":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T12:23:22Z","timestamp":1792412602000},"source":"Crossref","is-referenced-by-count":0,"title":["FMCerNet: Frequency-Aware Multi-Label Learning for Fine-Grained Cervical Cytology Screening"],"prefix":"10.1093","author":[{"given":"Linyun","family":"Zhou","sequence":"first","affiliation":[{"name":"Zhejiang University College of Computer Science, , Hangzhou, 310058, Zhejiang,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiuyu","family":"Cai","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital, Zhejiang University School of Medicine Department of Pathology, , Hangzhou, 310003, Zhejiang,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoling","family":"Wang","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital, Zhejiang University School of Medicine Department of Pathology, , Hangzhou, 310003, Zhejiang,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weihan","family":"Li","sequence":"additional","affiliation":[{"name":"Zhejiang University School of Software Technology, , Ningbo, 315100, Zhejiang,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Yang","sequence":"additional","affiliation":[{"name":"Zhejiang University School of Software Technology, , Ningbo, 315100, Zhejiang,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingli","family":"Song","sequence":"additional","affiliation":[{"name":"Zhejiang University College of Computer Science, , Hangzhou, 310058, Zhejiang,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital, Zhejiang University School of Medicine Department of Pathology, , Hangzhou, 310003, Zhejiang,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Zhou","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University International Peace Maternal and Child Health Hospital, School of Medicine, , Shanghai, 200030,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qihan","family":"You","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital, Zhejiang University School of Medicine Department of Pathology, , Hangzhou, 310003, Zhejiang,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yudong","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University International Peace Maternal and Child Health Hospital, School of Medicine, , Shanghai, 200030,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zunlei","family":"Feng","sequence":"additional","affiliation":[{"name":"Zhejiang University School of Software Technology, , Ningbo, 315100, Zhejiang,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiuming","family":"Zhang","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital, Zhejiang University School of Medicine Department of Pathology, , Hangzhou, 310003, Zhejiang,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,10,19]]},"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btag759\/72109238\/btag759.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btag759\/72109238\/btag759.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T12:23:22Z","timestamp":1792412602000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article\/doi\/10.1093\/bioinformatics\/btag759\/8943329"}},"subtitle":[],"editor":[{"given":"Virginie","family":"Uhlmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2026,10,19]]},"references-count":0,"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btag759","relation":{},"ISSN":["1367-4811"],"issn-type":[{"value":"1367-4811","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,19]]},"article-number":"btag759"}}