{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T14:30:24Z","timestamp":1791469824492,"version":"4.3.4"},"reference-count":49,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T00:00:00Z","timestamp":1672185600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100018594","name":"Central University Basic Research Fund of China","doi-asserted-by":"publisher","award":["2042021kf0174"],"award-info":[{"award-number":["2042021kf0174"]}],"id":[{"id":"10.13039\/501100018594","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018594","name":"Central University Basic Research Fund of China","doi-asserted-by":"publisher","award":["2042021kf0216"],"award-info":[{"award-number":["2042021kf0216"]}],"id":[{"id":"10.13039\/501100018594","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82072996"],"award-info":[{"award-number":["82072996"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82103333"],"award-info":[{"award-number":["82103333"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Oral Diseases"],"published-print":{"date-parts":[[2023,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Imaging interpretation of the benignancy or malignancy of parotid gland tumors (PGTs) is a critical consideration prior to surgery in view of therapeutic and prognostic values of such discrimination. This study investigates the application of a deep learning\u2010based method for preoperative stratification of PGTs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>Using the 3D DenseNet\u2010121 architecture and a dataset consisting of 117 volumetric arterial\u2010phase contrast\u2010enhanced CT scans, we developed a binary classifier for PGT distinction and tested it. We compared the discriminative performance of the model on the test set to that of 12 junior and 12 senior head and neck clinicians. Besides, potential clinical utility of the model was evaluated by measuring changes in unassisted and model\u2010assisted performance of junior clinicians.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The model finally reached the sensitivity, specificity, PPV, NPV, F1\u2010score of 0.955 (95% CI 0.751\u20130.998), 0.667 (95% CI 0.241\u20130.940), 0.913 (95% CI 0.705\u20130.985), 0.800 (95% CI 0.299\u20130.989) and 0.933, respectively, comparable to that of practicing clinicians. Furthermore, there were statistically significant increases in junior clinicians' specificity, PPV, NPV and F1\u2010score in differentiating benign from malignant PGTs when unassisted and model\u2010assisted performance of junior clinicians were compared.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our results provide evidence that deep learning\u2010based method may offer assistance for PGT's binary distinction.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/odi.14474","type":"journal-article","created":{"date-parts":[[2022,12,15]],"date-time":"2022-12-15T12:10:03Z","timestamp":1671106203000},"page":"3325-3336","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Deep learning\u2010assisted diagnosis of parotid gland tumors by using contrast\u2010enhanced CT imaging"],"prefix":"10.1111","volume":"29","author":[{"given":"Xue\u2010Meng","family":"Shen","sequence":"first","affiliation":[{"name":"The State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei\u2010MOST) &amp; Key Laboratory of Oral Biomedicine Ministry of Education, School &amp; Hospital of Stomatology Wuhan University  Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Mao","sequence":"additional","affiliation":[{"name":"The State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei\u2010MOST) &amp; Key Laboratory of Oral Biomedicine Ministry of Education, School &amp; Hospital of Stomatology Wuhan University  Wuhan China"},{"name":"Department of Oral Maxillofacial\u2010Head Neck Oncology, School &amp; Hospital of Stomatology Wuhan University  Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhi\u2010Yi","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer Science Wuhan University  Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zi\u2010Kang","family":"Chai","sequence":"additional","affiliation":[{"name":"The State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei\u2010MOST) &amp; Key Laboratory of Oral Biomedicine Ministry of Education, School &amp; Hospital of Stomatology Wuhan University  Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ting\u2010Guan","family":"Sun","sequence":"additional","affiliation":[{"name":"The State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei\u2010MOST) &amp; Key Laboratory of Oral Biomedicine Ministry of Education, School &amp; Hospital of Stomatology Wuhan University  Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongchao","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer Science Wuhan University  Wuhan 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