{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T14:20:23Z","timestamp":1788877223514,"version":"build-2803163510"},"reference-count":40,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T00:00:00Z","timestamp":1768003200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T00:00:00Z","timestamp":1768003200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pediatric Blood &amp; Cancer"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Delayed chemotherapy\u2010induced nausea and vomiting (CINV) in pediatric oncology patients is currently under\u2010recognized. This study aims to develop, validate, and visualize a machine learning\u2010based model to predict delayed CINV risk in children.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Procedure<\/jats:title>\n                    <jats:p>This prospective cohort study was conducted from November 2021 to December 2022 at a tertiary hospital in southern China. Pediatric delayed CINV data were collected via an electronic diary using the Pediatric Nausea Assessment Tool (PeNAT) and National Cancer Institute\u2014Common Terminology Criteria for Adverse Events (NCI\u2010CTCAE) (v4.03), with PeNAT \u22653 or CTCAE grade \u22652 as the primary outcomes. Seven machine learning models, including random forest, support vector machine, and artificial neural network (ANN), were developed and validated using 29 sociodemographic and clinical features. Model performance was assessed using the area under the receiver operating characteristic curve (AUC) and other metrics. Shapley's Additive Explanations (SHAP) enhanced interpretability, and the models were integrated into a web\u2010based calculator for visualization.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Overall, 399 pediatric patients (60.4% male; aged 4\u201318 years) were included. The AUC of the seven models ranged from 0.782 to 0.815, with the ANN model performing best (AUC 0.815; 95% CI, 0.695\u20130.903). The ANN model's global SHAP plot revealed that the most influential features were acute CINV, days of chemotherapy, age, number of recreational activities, expectancy of CINV, and control effectiveness of CINV. The ANN model was then deployed as a web\u2010based risk calculator for pediatric delayed CINV.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The ANN model demonstrated good performance in identifying children at high risk of delayed CINV. Our web\u2010based calculator provides a reliable tool for clinical staff to support targeted CINV management.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/1545-5017.70123","type":"journal-article","created":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T11:25:53Z","timestamp":1768044353000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Machine Learning\u2010Based Prediction Model for Delayed Chemotherapy\u2010Induced Nausea and Vomiting in Pediatric Cancer: A Prospective Cohort Study"],"prefix":"10.1002","volume":"73","author":[{"given":"Jun","family":"Deng","sequence":"first","affiliation":[{"name":"State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer Sun Yat\u2010sen University Cancer Center  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyu","family":"Lou","sequence":"additional","affiliation":[{"name":"School of Nursing Sun Yat\u2010sen University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longzhen","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer Sun Yat\u2010sen University Cancer Center  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meixia","family":"Zhong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer Sun Yat\u2010sen University Cancer Center  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siying","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer Sun Yat\u2010sen University Cancer Center  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yulian","family":"Zeng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer Sun Yat\u2010sen University Cancer Center  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengxiao","family":"Jiang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer Sun Yat\u2010sen University Cancer Center  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huijie","family":"Guan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer Sun Yat\u2010sen University Cancer Center  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruiqing","family":"Cai","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer Sun Yat\u2010sen University Cancer Center  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,1,10]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.phoj.2023.07.003"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1097\/NCC.0b013e3182281493"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ctarc.2020.100278"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1093\/annonc\/mdh110"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1097\/j.pbj.0000000000000234"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1177\/10781552221122026"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/djx250"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejon.2022.102121"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/pbc.27646"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/pbc.30001"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1093\/annonc\/mdx100"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamaoncol.2015.3730"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/pbc.27584"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.20.00134"},{"key":"e_1_2_11_16_1","article-title":"Pediatric Related Risk Factors in Acute and Delayed Chemotherapy\u2010Induced Nausea and Vomiting: Multivariate Analysis","volume":"18","author":"Albuquerque A. 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