Can we use machine learning to improve the interpretation and application of urodynamic data?: ICI-RS 2023.

Journal: Neurourology and urodynamics
PMID: 37921238

Abstract

INTRODUCTION: A "Think Tank" at the International Consultation on Incontinence-Research Society meeting held in Bristol, United Kingdom in June 2023 considered the progress and promise of machine learning (ML) applied to urodynamic data.

Authors

  • Andrew Gammie
    Bristol Urological Institute, Southmead Hospital, Bristol, UK.
  • Salvador Arlandis
    Urology Department, Hospital Universitario y Politécnico La Fe, Valencia, Spain.
  • Bruna M Couri
    Laborie Medical Technologies, Portsmouth, New Hampshire, USA.
  • Michael Drinnan
    Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK.
  • D Carolina Ochoa
    Bristol Urological Institute, Southmead Hospital, Bristol, UK.
  • Angie Rantell
    Urogynaecology Department, King's College Hospital, London, UK.
  • Mathijs de Rijk
    Department of Urology, Maastricht University, Maastricht, The Netherlands.
  • Thomas van Steenbergen
    University Medical Center Utrecht, Utrecht, The Netherlands.
  • Margot Damaser
    The Cleveland Clinic, Cleveland, Ohio, USA.

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