Prediction of operation time in percutaneous nephrolithotomy (PCNL) patients: A machine learning approach
Stone-free status followed by stone burden and gender are critical predictors of PCNL operation time. Achieving stone-free status significantly reduces procedure duration. Machine learning models, particularly eXtreme Gradient Boosting, provide valuable predictive insights, aiding in surgical planning and optimizing patient outcomes.
Authors
- Owais Ghammaz (ORCID: https://orcid.org/0009-0004-8914-6483)
- Azhar Al-Alwani
- Nabil Ardah
- Rami Al-Azab
- Mohammed Jalal Akel
- Bashar Tayyem
- Nazih Alhirtani
- Abdallah Bakeer
- Bader Al-Deen Anabtawi
- Eyas Amaierh
Institutions
- Jordan University of Science and Technology (JO)
- King Abdullah University Hospital (JO)
Publication Details
- Journal
- Urologia Journal
- Published
- 2025-05-17
- DOI
- https://doi.org/10.1177/03915603251338720
- Citations
- 1
- Primary Topic
- Kidney Stones and Urolithiasis Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.52