AUA 2023 Stone Disease

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AUA 2023: Machine Learning Prediction of Symptomatic Kidney Stone Recurrence Using 24-Hour Urine Data and Electronic Health Record Derived Features

AUA 2023: A Novel Machine-Learning Algorithm to Predict Stone Recurrence with 24-hour Urine Data

AUA 2023: Ureteral Stent Biomaterial Encrustation after Endoscopic Surgery: A Prospective Randomized Study

AUA 2023: Efficacy and Safety of a Magnetic Hydrogel for Stone Fragment Removal: An In Vitro and In Vivo Study

AUA 2023: State of the Art Lecture: Over-the-Counter Remedies for Recurrent Stone Formers: Where Is the Evidence?

AUA 2023: State-of-the-art Lecture: Treatment of Fungal Urinary Tract Infections

AUA 2023: State of the Art Lecture: Regenerative Medicine in Sexual Medicine: The Hard Facts

AUA 2023: John K. Lattimer Lecture Innovation in Urology: From a Seminal “Why” to a Functional “How”

AUA 2023: Second Opinion Cases – The Growing Problem of Antibiotic Resistance for Urinary Tract Infection in Geriatrics

AUA 2023: Crossfire: Controversy in Urology: Is standard PCNL dead?

AUA 2023: Laser-Guided Renal Access for PCNL: A Comparison to Conventional Renal Access

AUA 2023: A Single Centre Prospective Randomized Controlled Study to Assess Outcomes and Complications of Conventional Stent Placement Versus No Stent Placement after Ureteroscopy for Distal Ureteric Calculus of Size 1 cms

AUA 2023: Automated Surgical Skills Assessment: Consensus Building Towards Human-derived Ground Truth Scores for Machine Learning Algorithms

AUA 2023: Follow-up 24-Hour Urine Studies During and Post-COVID-19 Pandemic

AUA 2023: Machine Learning Model to Predict Likelihood of Spontaneous Ureteral Stone Passage

AUA 2023: Antimicrobial and Antibiofilm Properties of Chitosan: An Ex-Vivo Study on Kidney Stones

AUA 2023: Developing an Artificial Intelligence Model to Predict Differential Renal Function using Contrast-Enhanced CT Scans