{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:48:00Z","timestamp":1777596480749,"version":"3.51.4"},"reference-count":41,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T00:00:00Z","timestamp":1732838400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Reports"],"published-print":{"date-parts":[[2024,12]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>H\u00fcrthle cell (HCC) and columnar cell variants (CCV) are rare subtypes of thyroid cancer.<\/jats:p><\/jats:sec><jats:sec><jats:title>Aims<\/jats:title><jats:p>This study used machine learning (ML) to evaluate treatment effectiveness and develop prognostic models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Chi\u2010square tests, Kaplan\u2013Meier curves, log\u2010rank tests, and Cox regression were used. Five ML algorithms constructed prognostic models predicting 5\u2010year survival, validated using the AUC of the ROC curve.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Among 3690 patients, 3180 had CCV and 510 had HCC. ML models showed metastasis, surgery + RT, and age were significant factors for HCC, while the N component of TNM, metastasis, and tumor size were significant for CCV.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This study offers a comprehensive approach for treating and assessing prognosis in PTC variants. The ML models developed offer practical tools for personalized clinical decision\u2010making.<\/jats:p><\/jats:sec>","DOI":"10.1002\/cnr2.70071","type":"journal-article","created":{"date-parts":[[2024,11,30]],"date-time":"2024-11-30T06:40:13Z","timestamp":1732948813000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Prognostic Models Using Machine Learning Algorithms and Treatment Outcomes of Papillary Thyroid Carcinoma Variants"],"prefix":"10.1002","volume":"7","author":[{"given":"Sakhr","family":"Alshwayyat","sequence":"first","affiliation":[{"name":"Research Associate King Hussein Cancer Center  Amman Jordan"},{"name":"Internship Princess Basma Teaching Hospital  Irbid Jordan"},{"name":"Applied Science Research Center Applied Science Private University  Amman Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haya","family":"Kamal","sequence":"additional","affiliation":[{"name":"Faculty of 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