Drainage in ureteropelvic junction obstruction, Hydronephrosis.
| Article DOI | https://doi.org/10.1109/ISBI48211.2021.9434129 |
| Objective | To predict severe ureteropelvic junction obstruction from renal US images |
| AI Approach | CNN |
| Data Source(s) | Single institutional series (54 US images) |
| Model Input | Renal US, coronal image |
| Model Outcome | T 1/2 > 20 minutes |
| Model Metrics | Accuracy: 78% Sensitivity 62% Specificity 83% |
| Model Usability | NA |
AI = Artificial intelligence, UPJO = Ureteropelvic junction obstruction, SFU = Society for Fetal Urology, CNN = Convolutional Neural Network
AIPEDURO 
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