Use of Temporally Validated Machine Learning Models To Predict Outcomes of Percutaneous Nephrolithotomy Using Data from the British Association of Urological Surgeons Percutaneous Nephrolithotomy Audit.

Journal: European urology focus
PMID: 38307805

Abstract

BACKGROUND AND OBJECTIVE: Machine learning (ML) is a subset of artificial intelligence that uses data to build algorithms to predict specific outcomes. Few ML studies have examined percutaneous nephrolithotomy (PCNL) outcomes. Our objective was to build, streamline, temporally validate, and use ML models for prediction of PCNL outcomes (intensive care admission, postoperative infection, transfusion, adjuvant treatment, postoperative complications, visceral injury, and stone-free status at follow-up) using a comprehensive national database (British Association of Urological Surgeons PCNL).

Authors

  • Robert M Geraghty
    Department of Urology, Freeman Hospital, Newcastle upon Tyne, UK; Institute of Genetic Medicine, International Centre for Life, Newcastle University, Newcastle upon Tyne, UK. Electronic address: rob.geraghty@newcastle.ac.uk.
  • Anshul Thakur
    School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India; Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, Tennessee.
  • Sarah Howles
    Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.
  • William Finch
    Department of Urology, Norfolk and Norwich University Hospital, Norwich, UK.
  • Sarah Fowler
    Comparative Audit Service, Royal College of Surgeons of England, London, UK.
  • Alistair Rogers
    Department of Urology, Freeman Hospital, Newcastle upon Tyne, UK.
  • Seshadri Sriprasad
    Department of Urology, Dartford and Gravesham NHS Trust, Dartford, UK.
  • Daron Smith
    Institute of Urology, University College Hospital London, London, UK.
  • Andrew Dickinson
    Department of Urology, University Hospitals Plymouth NHS Trust, Plymouth, UK.
  • Zara Gall
    Department of Urology, Stockport NHS Foundation Trust, Stockport, UK.
  • Bhaskar K Somani
    University Hospital Southampton NHS Trust, Southampton, Hampshire, UK.

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