{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T05:45:58Z","timestamp":1792043158929,"version":"4.4.0"},"reference-count":41,"publisher":"Wiley","issue":"17","license":[{"start":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T00:00:00Z","timestamp":1692748800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T00:00:00Z","timestamp":1692748800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81102447"],"award-info":[{"award-number":["81102447"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81501057"],"award-info":[{"award-number":["81501057"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81971173"],"award-info":[{"award-number":["81971173"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010041","name":"Tianjin Municipal Science and Technology Committee","doi-asserted-by":"publisher","award":["16JCQNJC10600"],"award-info":[{"award-number":["16JCQNJC10600"]}],"id":[{"id":"10.13039\/501100010041","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Medicine"],"published-print":{"date-parts":[[2023,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aims to develop a risk prediction model for chemotherapy\u2010induced nausea and vomiting (CINV) in cancer patients receiving highly emetogenic chemotherapy (HEC) and identify the variables that have the most significant impact on prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Data from Tianjin Medical University General Hospital were collected and subjected to stepwise data preprocessing. Deep learning algorithms, including deep forest, and typical machine learning algorithms such as support vector machine (SVM), categorical boosting (CatBoost), random forest, decision tree, and neural network were used to develop the prediction model. After training the model and conducting hyperparameter optimization (HPO) through cross\u2010validation in the training set, the performance was evaluated using the test set. Shapley additive explanations (SHAP), partial dependence plot (PDP), and Local Interpretable Model\u2010Agnostic Explanations (LIME) techniques were employed to explain the optimal model. Model performance was assessed using AUC, F1 score, accuracy, specificity, sensitivity, and Brier score.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The deep forest model exhibited good discrimination, outperforming typical machine learning models, with an AUC of 0.850 (95%CI, 0.780\u20130.919), an F1 score of 0.757, an accuracy of 0.852, a specificity of 0.863, a sensitivity of 0.784, and a Brier score of 0.082. The top five important features in the model were creatinine clearance (Ccr), age, gender, anticipatory nausea and vomiting, and antiemetic regimen. Among these, Ccr had the most significant predictive value. The risk of CINV decreased with increased Ccr and age, while it was higher in the presence of anticipatory nausea and vomiting, female gender, and non\u2010standard antiemetic regimen.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The deep forest model demonstrated good discrimination in predicting the risk of CINV in cancer patients prescribed HEC. Kidney function, as represented by Ccr, played a crucial role in the model's prediction. The clinical application of this predictive tool can help assess individual risks and improve patient care by proactively optimizing the use of antiemetics in cancer patients receiving HEC.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cam4.6428","type":"journal-article","created":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T04:39:31Z","timestamp":1692765571000},"page":"18306-18316","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["A deep learning\u2010based interpretable decision tool for predicting high risk of chemotherapy\u2010induced nausea and vomiting in cancer patients prescribed highly emetogenic chemotherapy"],"prefix":"10.1002","volume":"12","author":[{"given":"Jingyue","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Pharmacy Tianjin Medical University General Hospital  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xudong","family":"Cui","sequence":"additional","affiliation":[{"name":"School of Mathematics Tianjin University  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chong","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Pharmacy Tianjin Medical University General Hospital  Tianjin China"},{"name":"Department of Pharmacy Tianjin Huanhu Hospital  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diansheng","family":"Zhong","sequence":"additional","affiliation":[{"name":"Department of Medical Oncology Tianjin Medical University General Hospital  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yinjuan","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Medical Oncology Tianjin Medical University General Hospital  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoxiong","family":"Yue","sequence":"additional","affiliation":[{"name":"Academy of Medical Engineering and Translational Medicine Tianjin University  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gaoshuang","family":"Lan","sequence":"additional","affiliation":[{"name":"Department of Pharmacy Tianjin Medical University General Hospital  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linlin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Medical Oncology Tianjin Medical University General Hospital  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liangfu","family":"Lu","sequence":"additional","affiliation":[{"name":"Academy of Medical Engineering and Translational Medicine Tianjin University  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7132-5572","authenticated-orcid":false,"given":"Hengjie","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Pharmacy Tianjin Medical University General Hospital  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,8,23]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra0706547"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00520-012-1448-1"},{"key":"e_1_2_10_4_1","unstructured":"National Comprehensive Cancer Network (NCCN) clinical practice guidelines in oncology: antiemesis [v2.2023]. 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