SynthesisUrologie (Heidelberg, Germany)2026
[Artificial intelligence in urological surgery].
Synthesis in Urologie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe integration of artificial intelligence (AI) into urological robotic surgery is currently in a dynamic phase of development and validation. Minimally invasive, standardized, and video-based procedures create highly data-rich operative environments with clearly defined workflow steps, thereby providing ideal conditions for the development of AI-based systems.
objectiveThe objective of this work is to present the current state of AI integration in urological robotic surgery, to classify existing clinically available applications, and to critically evaluate the perspective of autonomous systems. Technological, regulatory, and clinical aspects are considered in equal measure. MATERIALS AND
methodsAn analysis of the current literature was conducted, along with a systematic review of clinically available robotic platforms and experimental systems. Both approved medical devices with integrated AI functionalities and preclinical developments in the field of semi-autonomous and autonomous surgical modules were included. In addition, international research initiatives aimed at advancing autonomous surgical systems were taken into account.
conclusionCurrent developments primarily focus on supportive systems such as environment modeling and augmented reality (AR) navigation. Clinically approved platforms increasingly benefit from data-driven performance analytics, optimized treatment planning, and enhanced teleoperative structures. As the level of autonomy increases, the requirements for validation, regulation, and liability frameworks also become more demanding. Urological robotic surgery is therefore undergoing a paradigm shift-from purely teleoperated assistance toward adaptive, semi-autonomous systems. This transition is driven not only by technological innovation but also by international research and investment programs, and it necessitates structural adaptations in surgical training, quality control, and legal frameworks.
Indexed as
Identifiers
42166019What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.