{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T13:00:50Z","timestamp":1791464450018,"version":"4.3.4"},"reference-count":40,"publisher":"The Endocrine Society","issue":"4","license":[{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"vor","delay-in-days":13,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2020M670063ZX"],"award-info":[{"award-number":["2020M670063ZX"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Health Committee of Sichuan Province","award":["20PJ061"],"award-info":[{"award-number":["20PJ061"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32101188"],"award-info":[{"award-number":["32101188"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"General Project of Science and Technology Department of Sichuan Province","award":["2021YFS0102"],"award-info":[{"award-number":["2021YFS0102"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,24]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Purpose<\/jats:title>\n                  <jats:p>This study investigates the efficiency of deep learning models in the automated diagnosis of Hashimoto\u2019s thyroiditis (HT) using real-world ultrasound data from ultrasound examinations by computer-assisted diagnosis (CAD) with artificial intelligence.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We retrospectively collected ultrasound images from patients with and without HT from 2 hospitals in China between September 2008 and February 2018. Images were divided into a training set (80%) and a validation set (20%). We ensembled 9 convolutional neural networks (CNNs) as the final model (CAD-HT) for HT classification. The model\u2019s diagnostic performance was validated and compared to 2 hospital validation sets. We also compared the accuracy of CAD-HT against seniors\/junior radiologists. Subgroup analysis of CAD-HT performance for different thyroid hormone levels (hyperthyroidism, hypothyroidism, and euthyroidism) was also evaluated.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>39 280 ultrasound images from 21 118 patients were included in this study. The accuracy, sensitivity, and specificity of the HT-CAD model were 0.892, 0.890, and 0.895, respectively. HT-CAD performance between 2 hospitals was not significantly different. The HT-CAD model achieved a higher performance (P &amp;lt; 0.001) when compared to senior radiologists, with a nearly 9% accuracy improvement. HT-CAD had almost similar accuracy (range 0.87-0.894) for the 3 subgroups based on thyroid hormone level.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>The HT-CAD strategy based on CNN significantly improved the radiologists\u2019 diagnostic accuracy of HT. Our model demonstrates good performance and robustness in different hospitals and for different thyroid hormone levels.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1210\/clinem\/dgab870","type":"journal-article","created":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T09:40:35Z","timestamp":1639561235000},"page":"953-963","source":"Crossref","is-referenced-by-count":35,"title":["Convolutional Neural Network-Based Computer-Assisted Diagnosis of Hashimoto\u2019s Thyroiditis on Ultrasound"],"prefix":"10.1210","volume":"107","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7732-6517","authenticated-orcid":false,"given":"Wanjun","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Thyroid Surgery, West China Hospital, Sichuan University, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingbo","family":"Kang","sequence":"additional","affiliation":[{"name":"West China Biomedical Big Data Center, West China Hospital, Sichuan 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