A Performance Comparison on the Machine Learning Classifiers in Predictive Pathology Staging of Prostate Cancer

摘要：

　　This study objectives to investigate a range of Partin table and several machine learning methods for pathological stage prediction and assess them with respect to their predictive model performance based on Koreans data.The data was used SPCDB and gathered records from 944 patients treated with tertiary hospital.Partin table has low accuracy(65.68%)when applied on SPCDB dataset for comparison on patients with OCD and NOCD conditions.SVM(75%)represents a promising alternative to Partin table from which pathology staging can benefit.

关键词： Prostate Cancer Machine Learning Pathology staging

作者: Jae Kwon Kim In Hye Yook Mun Joo Choi Jong Sik Lee Yong Hyun Park Ji Youl Lee In Young Choi

作者单位: Department of Computer Science and Information Engineering,Inha University,InhaRo 100,Nam-gu,Incheon Department of Urology,Seoul St.Marys Hospital,College of Medicine,The Catholic University of Korea,

会议类型: 国际会议

会议名称: 第十六届世界医药健康信息学大会((MEDINFO2017)、第二届世界医药健康信息学华语论坛(WCHIS 2017)、第15届全国医药信息学大会(CMIA 2017)

会议地点: 苏州

会议语种:英文

页码: 1273-1273

在线出版日期: 2017-08-21（万方平台首次上网日期，不代表论文的发表时间）