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A treatment prediction strategy for overactive bladder using a machine learning algorithm that utilized data from the FAITH study.
Hadi, Farid; Sumarsono, Budiwan; Lee, Kyu-Sung; Oh, Seung-June; Cho, Sung Tae; Hsu, Yu-Chao; Rasner, Paul; Jenkins, Cerys; Fisher, Harry.
Affiliation
  • Hadi F; Astellas Pharma Medical Affairs, Singapore, Singapore.
  • Sumarsono B; Astellas Pharma Medical Affairs, Singapore, Singapore.
  • Lee KS; Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
  • Oh SJ; Department of Urology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, South Korea.
  • Cho ST; Department of Urology, Hallym University Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, South Korea.
  • Hsu YC; Department of Urology, Linkou Chang Gung Memorial Hospital, Taipei, Taiwan.
  • Rasner P; Urological Department, Moscow State University of Medicine and Dentistry, Moscow, Russia.
  • Jenkins C; Human Data Sciences, Cardiff, UK.
  • Fisher H; Human Data Sciences, Cardiff, UK.
Neurourol Urodyn ; 42(6): 1227-1237, 2023 08.
Article in En | MEDLINE | ID: mdl-37148497
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Urinary Bladder, Overactive / Urological Agents Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Neurourol Urodyn Year: 2023 Document type: Article Affiliation country: Singapur Country of publication: Estados Unidos
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Urinary Bladder, Overactive / Urological Agents Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Neurourol Urodyn Year: 2023 Document type: Article Affiliation country: Singapur Country of publication: Estados Unidos