AIMC Topic: Spinal Dysraphism

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Machine Learning Analysis of Videourodynamics to Predict Incident Hydronephrosis in Patients With Spina Bifida.

The Journal of urology Mar 25, 2025
PURPOSE: Variability in the interpretation of videourodynamics studies limits reliable classification of kidney injury risk for patients with spina bifida. We developed machine learning models to predict incident hydronephrosis in patients with spina...
Humans Child Predictive Value of Tests Incidence Child, Preschool Hydronephrosis Spinal Dysraphism Video Recording Urodynamics Male Risk Assessment Young Adult Infant Adult Adolescent Machine Learning Female
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Machine Learning Algorithms for Prediction of Ambulation and Wheelchair Transfer Ability in Spina Bifida.

Archives of physical medicine and rehabilitation Dec 2, 2024
OBJECTIVE: To determine which statistical techniques enhance our ability to predict ambulation and transfer ability in people with spina bifida (SB).
Child, Preschool Child Middle Aged Adolescent Spinal Dysraphism Walking Wheelchairs Aged Young Adult Adult Male Retrospective Studies Female Algorithms Humans Neural Networks, Computer Machine Learning
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Editorial. Occult dysraphism, spinopelvic angles, and machine learning: applying new tools to complex unsolved problems in pediatric neurosurgery.

Journal of neurosurgery. Pediatrics Mar 1, 2024
Humans Machine Learning Child Spinal Dysraphism Neurosurgery Pediatrics Pelvis Neurosurgical Procedures
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Deep Learning of Videourodynamics to Classify Bladder Dysfunction Severity in Patients With Spina Bifida.

The Journal of urology Feb 14, 2023
PURPOSE: Urologists rely heavily on videourodynamics to identify patients with neurogenic bladders who are at risk of upper tract injury, but their interpretation has high interobserver variability. Our objective was to develop deep learning models o...
Spinal Dysraphism Urodynamics Deep Learning Urinary Bladder, Neurogenic Humans Urinary Bladder Child Cross-Sectional Studies
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Machine Learning for Urodynamic Detection of Detrusor Overactivity.

Urology Oct 29, 2021
OBJECTIVE: To develop a machine learning algorithm that identifies detrusor overactivity (DO) in Urodynamic Studies (UDS) in the spina bifida population. UDS plays a key role in assessment of neurogenic bladder in patients with spina bifida. Due to s...
Urinary Bladder, Overactive Spinal Dysraphism Child Urodynamics Adult Adolescent Machine Learning Infant Humans Child, Preschool Young Adult
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