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Various statistical analyses and feature selection techniques were applied to identify the most relevant radiomics features. Multiple machine learning models were trained and compared to build signatures for the intratumoral and each peritumoral region, along with a clinical signature. The performance of each model was evaluated using different metrics. Subsequently, a nomogram model was constructed by combining the best-performing radiomics and clinical models.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>In the testing cohort, the nomogram model exhibited an AUC of 0.816, outperforming the other models. The nomogram model\u2019s calibration curve showed good agreement between predicted and observed outcomes in both the training and testing sets. When predicting survival, the model\u2019s concordance index (C-index) was 0.888 in the training cohort and 0.899 in the testing cohort, indicating its robust predictive ability.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>In conclusion, the combined nomogram model, incorporating radiomics and clinical features, outperformed other models in predicting treatment response and survival outcomes for LA-NPC patients receiving induction chemotherapies. These findings highlight the potential clinical utility of the model, suggesting its value in individualized treatment planning and decision-making.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s00432-023-05590-5","type":"journal-article","created":{"date-parts":[[2024,1,29]],"date-time":"2024-01-29T17:03:26Z","timestamp":1706547806000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["CT-based peritumoral radiomics nomogram on prediction of response and survival to induction chemotherapy in locoregionally advanced nasopharyngeal carcinoma"],"prefix":"10.1007","volume":"150","author":[{"given":"Fanyuan","family":"Zeng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhuomiao","family":"Ye","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qin","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,29]]},"reference":[{"key":"5590_CR1","doi-asserted-by":"publisher","first-page":"11","DOI":"10.2214\/AJR.11.6954","volume":"198","author":"A Abdel Khalek Abdel Razek","year":"2012","unstructured":"Abdel Khalek Abdel Razek A, King A (2012) MRI and CT of nasopharyngeal carcinoma. 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