Complications after surgery in UPJO
| Article DOI | https://doi.org/10.1007/s00345-025-05552-1 |
| Objective | To predict complications after laparoscopic surgery for UPJO |
| AI Approach | LR, KNN, SVM, Decision Tree, RF, XGBoost, CNN |
| Data Source(s) | Single institutional series (526 patients) |
| Model Input | Pre-operative UTI, calculus, renal cortical thickness, collecting system, time of removal of DJ, removal of drainage, white blood cell count |
| Model Outcome | Post-operative UTI Post-operative recurrence |
| Model Metrics | Post-operative UTI (Random Forrest): AUC 0.93 Post-operative recurrence (Random Forrest): AUC 0.89 |
| Model Usability | Dataset available upon request to authors. |
AI = Artificial intelligence, UPJO = Ureteropelvic junction obstruction, AUC = Area under the receiver operator characteristic
AIPEDURO 
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