default author photo

Daniel Alvarez

Stanford University

367 Panama St

Stanford, CA 94305

United States

SCHOLARLY PAPERS

1

DOWNLOADS

100

TOTAL CITATIONS

0

Scholarly Papers (1)

1.

Effective Assessment of Pediatric Antenatal Hydronephrosis Patients Using a Clinical Deep Learning Algorithm

Number of pages: 41 Posted: 07 Dec 2021
University of Toronto - Department of Genetics and Genome Biology, University of Toronto - Division of Urology, University of Toronto - Department of Genetics and Genome Biology, Stanford University, Stanford University, Stanford University, St. Luke's Medical Center (SLMC) - Institute of Urology, University of Toronto - Division of Urology, University of Toronto - Division of Urology, University of Toronto - Division of Nephrology, University of Iowa, University of Iowa, University of Toronto - Department of Genetics and Genome Biology and University of Toronto - Division of Urology
Downloads 100 (689,572)

Abstract:

Loading...

antenatal hydronephrosis, pediatric surgery, pediatric nephrology, pediatric urology, Machine Learning, deep learning