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Prediction of the composition of urinary stones using deep learning.
Kim, Ui Seok; Kwon, Hyo Sang; Yang, Wonjong; Lee, Wonchul; Choi, Changil; Kim, Jong Keun; Lee, Seong Ho; Rim, Dohyoung; Han, Jun Hyun.
Afiliação
  • Kim US; Department of Urology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea.
  • Kwon HS; Department of Urology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea.
  • Yang W; Department of Urology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea.
  • Lee W; Department of Urology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea.
  • Choi C; Department of Urology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea.
  • Kim JK; Department of Urology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea.
  • Lee SH; Department of Urology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea.
  • Rim D; Department of Cognitive Science, Yonsei University, Seoul, Korea.
  • Han JH; Department of Urology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea. junuro@naver.com.
Investig Clin Urol ; 63(4): 441-447, 2022 07.
Article em En | MEDLINE | ID: mdl-35670006
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cálculos Urinários / Urolitíase / Aprendizado Profundo Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Investig Clin Urol Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cálculos Urinários / Urolitíase / Aprendizado Profundo Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Investig Clin Urol Ano de publicação: 2022 Tipo de documento: Article