Integration of novel artificial intelligence tools in pediatric urologic practice

Area of Science:

• Pediatric Urology
• Medical Technology
• Artificial Intelligence

Background:

• Artificial intelligence (AI) is rapidly advancing in healthcare.
• There's a growing interest in AI applications within pediatric urology.
• AI is proposed as a solution for various healthcare challenges.

Purpose of the Study:

• To review current AI tools available for pediatric urologists.
• To preview emerging AI technologies in the field.
• To highlight studies on AI benefits and limitations in pediatric urology practice.

Main Methods:

• Literature review of AI applications in pediatric urology.
• Analysis of current and upcoming AI technologies.
• Examination of research studies on AI in clinical practice.

Main Results:

• Imaging-driven AI software and clinical prediction tools are key applications.
• AI enhances risk stratification for patients with chronic diseases and surgical needs.
• AI is utilized in enuresis treatment product development; large language models show promise but lack accuracy for patient education.

Conclusions:

• AI and machine learning (ML) are being explored for patient interface, imaging, and outcomes prediction in pediatric urology.
• ML is a promising clinical tool with the potential to transform healthcare systems.
• Most AI systems are still in preclinical stages but show significant future potential.