{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T17:45:55Z","timestamp":1788457555330,"version":"build-2803163510"},"reference-count":19,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2023,5,24]],"date-time":"2023-05-24T00:00:00Z","timestamp":1684886400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Head &amp; Neck"],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>Little information is available about deep learning methods used in ultrasound images of salivary gland tumors. We aimed to compare the accuracy of the ultrasound\u2010trained model to computed tomography or magnetic resonance imaging trained model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and methods<\/jats:title><jats:p>Six hundred and thirty\u2010eight patients were included in this retrospective study. There were 558 benign and 80 malignant salivary gland tumors. A total of 500 images (250 benign and 250 malignant) were acquired in the training and validation set, then 62 images (31 benign and 31 malignant) in the test set. Both machine learning and deep learning were used in our model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The test accuracy, sensitivity, and specificity of our final model were 93.5%, 100%, and 87%, respectively. There were no over fitting in our model as the validation accuracy was similar with the test accuracy.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The sensitivity and specificity were comparable with current MRI and CT images using artificial intelligence.<\/jats:p><\/jats:sec>","DOI":"10.1002\/hed.27396","type":"journal-article","created":{"date-parts":[[2023,5,24]],"date-time":"2023-05-24T07:46:30Z","timestamp":1684914390000},"page":"1885-1893","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Neural network combining with clinical ultrasonography: A new approach for classification of salivary gland tumors"],"prefix":"10.1002","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0858-0938","authenticated-orcid":false,"given":"Cheng\u2010Hung","family":"Tu","sequence":"first","affiliation":[{"name":"Department of Otorhinolaryngology \u2013 Head and Neck Surgery Changhua Christian Hospital  Changhua Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui\u2010Teng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics National Chung Hsing University  Taichung Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo\u2010Sen","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics National Chung Hsing University  Taichung Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chih\u2010En","family":"Kuo","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics National Chung Hsing University  Taichung Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9214-142X","authenticated-orcid":false,"given":"En\u2010Ying","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology \u2013 Head and Neck Surgery Changhua Christian Hospital  Changhua Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ching\u2010Ting","family":"Tu","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics National Chung Hsing University  Taichung Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wan\u2010Nien","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology \u2013 Head and Neck Surgery Changhua Christian Hospital  Changhua Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,5,24]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0194-5998(99)70323-2"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.3389\/fsurg.2018.00039"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.otc.2015.10.004"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1097\/CCO.0b013e328344f59c"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11547-017-0813-z"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A6625"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1177\/0194599816687744"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1001\/archotol.129.9.929"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.otohns.2007.05.062"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.oooo.2014.10.020"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms5006"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.21037\/tcr.2016.07.18"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2012.02.023"},{"key":"e_1_2_10_16_1","unstructured":"SimonyanK ZissermanA.Very deep convolutional networks for large\u2010scale image recognition. arXiv preprint arXiv:1409.1556."},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-76389-4"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2022.919088"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.632104"},{"key":"e_1_2_10_20_1","article-title":"The diagnostic value of ultrasound\u2010based deep learning in differentiating parotid gland tumors","volume":"2022","author":"Wang Y","year":"2022","journal-title":"J Oncol"}],"container-title":["Head &amp; 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