AI for BPH Surgical Decision-Making: Cost Effectiveness and Outcomes.

Journal: Current urology reports
PMID: 39312102

Abstract

PURPOSE OF REVIEW: Benign prostatic hyperplasia (BPH) is prevalent in nearly 70% of men over the age of 60, leading to significant clinical challenges due to varying symptom presentations and treatment responses. The decision to undergo surgical intervention is not straightforward; the American Urological Association recommends consideration of surgical treatment after inadequate or failed response to medical therapy. This review explores the role of artificial intelligence (AI), including machine learning and deep learning models, in enhancing the decision-making processes for BPH management.

Authors

  • John Lama
    Weill Cornell Medical College, New York City, NY, USA.
  • Joshua Winograd
    Weill Cornell Medical College, New York City, NY, USA.
  • Alia Codelia-Anjum
    Department of Urology, Northwell Health, Manhasset, NY, USA.
  • Naeem Bhojani
    Division of Urology, Centre Hospitalier de l'Université de Montréal (CHUM), Université de Montréal, Montreal, QC, Canada.
  • Dean Elterman
    Division of Urology, University of Toronto, Toronto, Canada.
  • Kevin C Zorn
    Section of Urology, Department of Surgery, University of Montreal Hospital Center, Montreal, QC, Canada.
  • Bilal Chughtai
    Department of Urology, Weill Cornell Medical College/New York Presbyterian, New York, NY, USA.

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