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Urinary Tract Calculi VI: Surgical Management

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Updated: May 22, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

[Artificial intelligence in urological surgery].

Sami-Ramzi Leyh-Bannurah^1,2,3, Felix Chun⁴, Hendrik Borgmann⁵

¹Klinik und Poliklinik für Urologie am UKE, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Deutschland. s.bannurah@googlemail.com.

Urologie (Heidelberg, Germany)

|May 21, 2026

Summary

This summary is machine-generated.

Artificial intelligence (AI) is transforming urological robotic surgery, moving from teleoperated assistance to adaptive, semi-autonomous systems. This shift requires updates in training, quality control, and legal frameworks for AI integration.

Keywords:

Augmented reality Computer vision Haptic feedback Surgical autonomy Tele-Surgery

Related Experiment Videos

Last Updated: May 22, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Area of Science:

Robotics
Artificial Intelligence
Urology

Background:

Urological robotic surgery is a data-rich environment ideal for AI development.
Current AI integration focuses on supportive systems and data-driven analytics.

Purpose of the Study:

To present the current state of AI in urological robotic surgery.
To classify existing AI applications and evaluate autonomous systems.
To consider technological, regulatory, and clinical aspects of AI integration.

Main Methods:

Literature analysis and systematic review of robotic platforms.
Inclusion of approved AI medical devices and preclinical developments.
Consideration of international research initiatives for autonomous surgical systems.

Main Results:

AI supports environment modeling and augmented reality (AR) navigation.
Clinically approved platforms utilize AI for performance analytics and treatment planning.
Increasing autonomy necessitates robust validation, regulation, and liability frameworks.

Conclusions:

Urological robotic surgery is shifting towards semi-autonomous systems.
Technological innovation and research programs drive this transition.
Adaptations in surgical training, quality control, and legal frameworks are essential.