{"title":"决策树和随机森林:生物数据分析中逻辑回归的非线性和非参数替代方案","authors":"Yoshiyasu Takefuji PhD","doi":"10.1016/j.jtho.2025.03.003","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":17515,"journal":{"name":"Journal of Thoracic Oncology","volume":"20 7","pages":"Pages e84-e85"},"PeriodicalIF":21.0000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Decision Trees and Random Forests: Nonlinear and Nonparametric Alternatives to Logistic Regression in Biological Data Analysis\",\"authors\":\"Yoshiyasu Takefuji PhD\",\"doi\":\"10.1016/j.jtho.2025.03.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":17515,\"journal\":{\"name\":\"Journal of Thoracic Oncology\",\"volume\":\"20 7\",\"pages\":\"Pages e84-e85\"},\"PeriodicalIF\":21.0000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Thoracic Oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1556086425001224\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Thoracic Oncology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1556086425001224","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
期刊介绍:
Journal of Thoracic Oncology (JTO), the official journal of the International Association for the Study of Lung Cancer,is the primary educational and informational publication for topics relevant to the prevention, detection, diagnosis, and treatment of all thoracic malignancies.The readship includes epidemiologists, medical oncologists, radiation oncologists, thoracic surgeons, pulmonologists, radiologists, pathologists, nuclear medicine physicians, and research scientists with a special interest in thoracic oncology.