Hydronephrosis severity, Hydronephrosis.
| Article DOI | https://doi.org/10.1016/j.jpurol.2023.05.014 |
| Objective | To diagnose and grade ureteropelvic junction oTo classify hydronephrosis on renal US imaging according to the SFU system |
| AI Approach | CNN |
| Data Source(s) | Single institutional series (710 children, 4659 ultrasound images) |
| Model Input | Sagittal and transverse renal images |
| Model Outcome | SFU Grade 0-4 |
| Model Metrics | SFU grade 0-IV: overall accuracy of 82% and within one grade accuracy of 98% |
| Model Usability | NA |
AI = Artificial intelligence, SFU = Society for Fetal Urology, CNN = Convolutional Neural Network
AIPEDURO 
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