Open AccessDevelopment and validation of a predictive model for the diagnosis of solid solitary pulmonary nodules using data mining methods
Author(s) -
Yangwei Xiang,
Yifeng Sun,
Yuan Liu,
Baohui Han,
Qunhui Chen,
Xiaodan Ye,
Li Zhu,
Wen Gao,
Wentao Fang
Publication year - 2019
Publication title -
journal of thoracic disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.682
H-Index - 60
eISSN - 2077-6624
pISSN - 2072-1439
DOI - 10.21037/jtd.2019.01.90
Subject(s) - support vector machine , logistic regression , cohort , medicine , malignancy , receiver operating characteristic , predictive value , artificial intelligence , random forest , cross validation , artificial neural network , machine learning , statistics , computer science , mathematics
The purpose of this study is to develop a predictive model to accurately predict the malignancy of solid solitary pulmonary nodule (SPN) by data mining methods.