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Comment on "Development and Validation of Risk Assessment Model for Pelvic Organ Prolapse Based on a Retrospective

Triwiyanto Triwiyanto1

  • 1Department of Medical Electronics Technology, Poltekkes Kemenkes Surabaya, Pucang Jajar Timur No. 10, Surabaya, East Java, Indonesia, 60245. triwi@poltekkes-surabaya.ac.id.

International Urogynecology Journal
|May 7, 2025
PubMed
Abstract

No abstract available in PubMed .

Keywords:
Machine learningPelvic organ prolapseRisk assessment modelShapley additive explanations method

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