{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T17:24:33Z","timestamp":1790875473178,"version":"4.1.0"},"reference-count":23,"publisher":"Portland Press Ltd.","issue":"4","license":[{"start":{"date-parts":[[2021,3,22]],"date-time":"2021-03-22T00:00:00Z","timestamp":1616371200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["portlandpress.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,4,30]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Objectives: The present study aimed to develop a random forest (RF) based prediction model for hyperuricemia (HUA) and compare its performance with the conventional logistic regression (LR) model. Methods: This cross-sectional study recruited 91,690 participants (14,032 with HUA, 77,658 without HUA). We constructed a RF-based prediction model in the training sets and evaluated it in the validation sets. Performance of the RF model was compared with the LR model by receiver operating characteristic (ROC) curve analysis. Results: The sensitivity and specificity of the RF models were 0.702 and 0.650 in males, 0.767 and 0.721 in females. The positive predictive value (PPV) and negative predictive value (NPV) were 0.372 and 0.881 in males, 0.159 and 0.978 in females. AUC of the RF models was 0.739 (0.728\u20130.750) in males and 0.818 (0.799\u20130.837) in females. AUC of the LR models were 0.730 (0.718\u20130.741) for males and 0.815 (0.795\u20130.835) for females. The predictive power of RF was slightly higher than that of LR, but was not statistically significant in females (Delong tests, P=0.0015 for males, P=0.5415 for females). Conclusion: Compared with LR, the good performance in HUA status prediction and the tolerance of features associations or interactions showed great potential of RF in further application. A prospective cohort is necessary for HUA developing prediction. People with high risk factors should be encouraged to actively control to reduce the probability of developing HUA.<\/jats:p>","DOI":"10.1042\/bsr20203859","type":"journal-article","created":{"date-parts":[[2021,3,22]],"date-time":"2021-03-22T15:39:26Z","timestamp":1616427566000},"update-policy":"https:\/\/doi.org\/10.1042\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Prediction model of random forest for the risk of hyperuricemia in a Chinese basic health checkup test"],"prefix":"10.1042","volume":"41","author":[{"given":"Yuhan","family":"Gao","sequence":"first","affiliation":[{"name":"Department of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, P.R. 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China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dihua","family":"Li","sequence":"additional","affiliation":[{"name":"Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Institute of Acute Abdominal Diseases, Tianjin Nankai Hospital, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Huang","sequence":"additional","affiliation":[{"name":"Senior Lecturer in Statistics, Hull York Medical School, University of Hull, Hull, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4478-878X","authenticated-orcid":false,"given":"Zhaowei","family":"Meng","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, P.R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Wang","sequence":"additional","affiliation":[{"name":"Tianjin University of Traditional Chinese Medicine, Jian Kang Chan Ye Yuan, Jinghai District, Tianjin, P.R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mei","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin Key Laboratory of Advanced Networking (TANK Lab), Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianyi","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin Key Laboratory of Advanced Networking (TANK Lab), Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin, P.R. 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China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Health Management, Tianjin Medical University General Hospital, Tianjin, P.R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xing","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Health Management, Tianjin Medical University General Hospital, Tianjin, P.R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaguang","family":"Fan","sequence":"additional","affiliation":[{"name":"Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, P.R. 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