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2022 Top Story in Urology: AI Meets Pediatric Urology: Observations From the Pediatric Urology Fall Congress
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- Weaver J, Logan J, Antony M, et al. Machine Learning Analysis of Equivocal Renal Scans to Predict Renal Complications. Abstract presented at: Pediatric Urology Fall Congress; October 20–23, 2022; Las Vegas, US. Accessed November 18, 2022.
- Erdman L, Rickard M, Drysdale E, et al. The Hydronephrosis Severity Index: A Multi-Site Validation of a Practical and Reliable Artificial Intelligence Tool for Rapid Follow-Up Decision-Making. Abstract presented at: Pediatric Urology Fall Congress; October 20–23, 2022; Las Vegas, US. Accessed November 18, 2022.
- Fernandez N, Chua M, Villanueva J, et al. Neural Network Non-Linear Modeling to Predict Hypospadias Genotype–Phenotype Correlation. Abstract presented at: Pediatric Urology Fall Congress; October 20–23, 2022; Las Vegas, US. Accessed November 18, 2022.
- Fairchild R, Aksenov L, Matias DM, et al. Using Machine Learning of Urodynamics to Predict Clinical Outcomes in Patients With Spina Bifida. Abstract presented at: Pediatric Urology Fall Congress; October 20–23, 2022; Las Vegas, US. Accessed November 18, 2022.
- Weaver J, Martin-olenski M, Logan J, et al. Deep Learning of Videourodynamics to Classify Bladder Dysfunction Severity. Abstract presented at: Pediatric Urology Fall Congress; October 20–23, 2022; Las Vegas, US. Accessed November 18, 2022.
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