Correspondence to - “A machine learning algorithm predicting risk of dilating VUR among infants with hydronephrosis using UTD classification”

We recently read the paper by Wang et al. with great interest, which is a single institutional study with 280 patients (540 renal units) using a machine learning-based model to differentiate which patients with prenatal hydronephrosis are most likely to “benefit” from VCUG, i.e., most likely to have high-grade reflux [1]. With the advent of better imaging techniques and greater awareness regarding routine prenatal imaging, the incidence of antenatally diagnosed cases of hydronephrosis has been increasing over the past decade.
Source: Journal of Pediatric Urology - Category: Urology & Nephrology Authors: Source Type: research