Vesicoureteral Reflux and Urinary Tract Infection
| Article DOI | https://doi.org/10.1159/000127342 |
| Objective | To predict the resolution of VUR |
| AI Approach | ANN |
| Data Source(s) | Institutional series (145 ureteric units) |
| Model Input | Age, sex, the cause and grade of VUR, the affected ureter, the type of treatment, existence of renal scar on DMSA scan, follow-up times, the number of injection |
| Model Outcome | VUR Resolution VUR Improvement VUR Persistent/Worse |
| Model Metrics | VUR Resolution: accuracy = 98% VUR Improvement: accuracy = 100% VUR Persistent/Worse: accuracy = 92% |
| Model Usability | NA |
AIPEDURO 
Leave a comment