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Papers

Machine learning prediction of stone-free success in patients with urinary stone after treatment of shock wave lithotripsy

http://10.1186/s12894-020-00662-x

  • AuthorHyun Seok Na,Jae Geun Lee,Jae Sung Lim,Ji Yong Lee,Jinbum Kim,Jong Mok Park,Ju Hyun Shin,Ki Hak Song,Long Jin,Seung Woo Yang,Yong Gil Na,전기완,하태영,현윤경
  • JournalBMC Urology (1471-2490), 20, 88 ~ -
  • Enrollment typeSCIE
  • publication date 20200703
The aims of this study were to determine the predictive value of decision support analysis for the shock wave lithotripsy (SWL) success rate and to analyze the data obtained from patients who underwent SWL to assess the factors influencing the outcome by using machine learning methods.