Risk Classification for Interstitial Cystitis/Bladder Pain Syndrome Using Machine Learning Based Predictions.

Journal: Urology
PMID: 38677373

Abstract

OBJECTIVE: To improve diagnosis of interstitial cystitis (IC)/bladder pain syndrome(IC) we hereby developed an improved IC risk classification using machine learning algorithms.

Authors

  • Laura E Lamb
    Oakland University William Beaumont School of Medicine, Rochester, MI; Strata Oncology, Ann Arbor, MI.
  • Joseph J Janicki
    Underactive Bladder Foundation, Pittsburgh, PA.
  • Sarah N Bartolone
    Corewell Health William Beaumont University Hospital, Royal Oak, MI.
  • Elijah P Ward
    Corewell Health William Beaumont University Hospital, Royal Oak, MI.
  • Nitya Abraham
    Montefiore Medical Center, Bronx, NY.
  • Melissa Laudano
    Montefiore Medical Center, Bronx, NY.
  • Christopher P Smith
    Baylor School of Medicine, Houston, TX.
  • Kenneth M Peters
    Oakland University William Beaumont School of Medicine, Rochester, MI; Underactive Bladder Foundation, Pittsburgh, PA; Corewell Health William Beaumont University Hospital, Royal Oak, MI.
  • Bernadette M M Zwaans
    Oakland University William Beaumont School of Medicine, Rochester, MI; Corewell Health William Beaumont University Hospital, Royal Oak, MI.
  • Michael B Chancellor
    Oakland University William Beaumont School of Medicine, Rochester, MI; Corewell Health William Beaumont University Hospital, Royal Oak, MI. Electronic address: Chancellormb@gmail.com.

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