{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T22:22:04Z","timestamp":1787610124592,"version":"build-2736575974"},"reference-count":47,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Third People's Hospital of Chengdu Clinical Research Program","award":["CSY-YN-01-2023-050"],"award-info":[{"award-number":["CSY-YN-01-2023-050"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Science Progress"],"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The incidence of cervical lymph node metastasis (CLNM) in thyroid cancer (TC) is high. Accurate preoperative diagnosis of CLNM is critical to reduce unnecessary lymph node dissection and complications for TC patients. Ultrasound (US)-based artificial intelligence (AI) systems show promise for CLNM prediction, but their diagnostic performance requires systematic evaluation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A comprehensive search of four electronic databases (Web of Science, Embase, PubMed, and Cochrane Library) was conducted from inception to 30 December 2023. The random-effects model was chosen to calculate the pooled diagnostic indicators. Sensitivity analysis and heterogeneity test were conducted.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among 19 included studies, the AI system demonstrated pooled sensitivity, specificity, area under the curve (AUC) were 0.76 (95% condidence interval (CI): 0.71\u20130.80), 0.78 (95% CI: 0.74\u20130.82), and 0.84 (95% CI: 0.15\u20130.99), respectively. The sensitivity, specificity and AUC in clinically node-negative (cN0) patients were 0.73 (95% CI: 0.68\u20130.77), 0.81 (95% CI: 0.76\u20130.85) and 0.83 (95% CI: 0.14\u20130.99). The sensitivity, specificity and AUC for the central CLNM were 0.73 (95% CI: 0.69\u20130.77), 0.77 (95% CI: 0.72\u20130.81) and 0.81 (95% CI: 0.14\u20130.99). Multi-center designed studies yielded higher sensitivity (0.79 vs. 0.75,\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      \u2009&lt;\u20090.01) and specificity (0.79 vs. 0.78,\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      \u2009&lt;\u20090.01) than single-center designs. Deep learning (DL) yielded higher sensitivity (0.79 vs. 0.74,\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      \u2009&lt;\u20090.01) and specificity (0.83 vs. 0.75,\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      \u2009&lt;\u20090.01) than classic machine learning. Studies published after 2022 yielded higher sensitivity (0.77 vs. 0.74,\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      \u2009&lt;\u20090.01) than before 2022. Studies from China had lower specificity than studies from other countries (0.78 vs. 0.80,\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      \u2009=\u20090.01). Models incorporating multimodal features outperformed unimodal US (specificity: 0.79 vs. 0.75,\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      \u2009&lt;\u20090.01).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>US-based AI systems exhibit favorable predictive value for CLNM in TC, particularly with DL and multimodal designs, potentially reducing overtreatment. Prospective validation is needed prior to clinical adoption.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/00368504251346906","type":"journal-article","created":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T03:08:21Z","timestamp":1750820901000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":9,"title":["Diagnostic performance of the ultrasound -based artificial intelligence diagnostic system in predicting cervical lymph node metastasis in patients with thyroid cancer: A systematic review and meta-analysis"],"prefix":"10.1177","volume":"108","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7012-3530","authenticated-orcid":false,"given":"Xueyao","family":"Tang","sequence":"first","affiliation":[{"name":"Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Zhou","sequence":"additional","affiliation":[{"name":"Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Liu","sequence":"additional","affiliation":[{"name":"Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shan","family":"Gao","sequence":"additional","affiliation":[{"name":"Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu"},{"name":"Department of Geriatric, Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,6,4]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecl.2018.10.002"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1245\/s10434-016-5225-0"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1210\/JC.2015-2084"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1038\/srep28414"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1089\/thy.2019.0587"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1002\/bjs.8985"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12020-013-9877-2"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.803986"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1089\/thy.2015.0020"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1245\/s10434-011-1600-z"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2021-051568"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.18632\/oncotarget.18915"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.11152\/mu-987"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.3390\/cancers14143357"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1002\/jum.14610"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.3390\/biomedicines12081676"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.nic.2021.04.002"},{"key":"e_1_3_3_19_2","article-title":"PRISMA 2020 Explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews","volume":"372","author":"Page MJ","year":"2021","unstructured":"Page MJ, Moher D, Bossuyt PM, et al. PRISMA 2020 Explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews. Br Med J 2021; 372: n160.","journal-title":"Br Med J"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-155-8-201110180-00009"},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.2147\/CMAR.S169741"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1089\/thy.2018.0082"},{"key":"e_1_3_3_23_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-18497-3"},{"key":"e_1_3_3_24_2","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2020.577537"},{"key":"e_1_3_3_25_2","doi-asserted-by":"publisher","DOI":"10.18280\/ts.380310"},{"key":"e_1_3_3_26_2","first-page":"7695","article-title":"Preoperative prediction of lymph node metastasis in patients with papillary thyroid carcinoma by an artificial intelligence algorithm","volume":"13","author":"Xia E","year":"2021","unstructured":"Xia E, Chi Y, Jin L, et al. Preoperative prediction of lymph node metastasis in patients with papillary thyroid carcinoma by an artificial intelligence algorithm. Am J Transl Res 2021; 13: 7695\u20137704.","journal-title":"Am J Transl Res"},{"key":"e_1_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2022.897596"},{"key":"e_1_3_3_28_2","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/ac4c47"},{"key":"e_1_3_3_29_2","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/7133972"},{"key":"e_1_3_3_30_2","doi-asserted-by":"publisher","DOI":"10.1002\/jum.16131"},{"key":"e_1_3_3_31_2","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2023.964074"},{"key":"e_1_3_3_32_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12885-023-10598-8"},{"key":"e_1_3_3_33_2","doi-asserted-by":"publisher","DOI":"10.21037\/qims-22-650"},{"key":"e_1_3_3_34_2","first-page":"1031","article-title":"Preoperative US integrated random forest model for predicting Delphian lymph node metastasis in patients with papillary thyroid cancer","volume":"19","author":"Zhou C","year":"2023","unstructured":"Zhou C, Xu C, Yang B, et al. Preoperative US integrated random forest model for predicting Delphian lymph node metastasis in patients with papillary thyroid cancer. Curr Med Imaging 2023; 19: 1031\u20131040.","journal-title":"Curr Med Imaging"},{"key":"e_1_3_3_35_2","doi-asserted-by":"publisher","DOI":"10.21037\/gs-23-349"},{"key":"e_1_3_3_36_2","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2023.1261080"},{"key":"e_1_3_3_37_2","doi-asserted-by":"publisher","DOI":"10.3233\/XST-230091"},{"key":"e_1_3_3_38_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13244-023-01550-2"},{"key":"e_1_3_3_39_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2019.01.006"},{"key":"e_1_3_3_40_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12916-024-03367-2"},{"key":"e_1_3_3_41_2","doi-asserted-by":"publisher","DOI":"10.21037\/gs-22-347"},{"key":"e_1_3_3_42_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-019-06098-8"},{"key":"e_1_3_3_43_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-019-06652-4"},{"key":"e_1_3_3_44_2","doi-asserted-by":"publisher","DOI":"10.1177\/1533033820969451"},{"key":"e_1_3_3_45_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2024.03.012"},{"key":"e_1_3_3_46_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-022-08956-4"},{"key":"e_1_3_3_47_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102629"},{"key":"e_1_3_3_48_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.surg.2005.09.013"}],"container-title":["Science Progress"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/00368504251346906","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/00368504251346906","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/00368504251346906","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T11:16:19Z","timestamp":1777634179000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/00368504251346906"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4]]},"references-count":47,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["10.1177\/00368504251346906"],"URL":"https:\/\/doi.org\/10.1177\/00368504251346906","relation":{},"ISSN":["0036-8504","2047-7163"],"issn-type":[{"value":"0036-8504","type":"print"},{"value":"2047-7163","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4]]},"article-number":"00368504251346906"}}