ReviewUrologie (Heidelberg, Germany)2025
[Digital urology : Possible uses for artificial intelligence and digital health applications].
Review in Urologie (Heidelberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- [Use of artificial intelligence in clinical practice and hospitals].Urologie (Heidelberg, Germany) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUrology presents itself as a modern and future-oriented discipline. Artificial intelligence (AI) is becoming increasingly important in the field of digital urology. It enables the analysis of large medical data sets, such as histological patterns, imaging or molecular markers. In addition, large language models (LLMs) are opening up new fields of application. Digital health applications (DiGA) are also becoming increasingly important.
objectivesThis article provides an overview of current developments in digital urology. The focus is on the possible applications of AI and LLMs, taking into account the legal and ethical framework, as well as an overview of the therapeutic landscape of DiGA in urological care.
methodsExisting AI models and applications will be presented and analyzed. In addition, DiGA in urological care and current regulatory requirements are discussed.
resultsAI systems can improve many areas of urology-for example through automated evaluation of image morphology and histology data or voice-based applications in documentation and communication. DiGA support the follow-up care and treatment of urological diseases. Their use requires transparency, data protection, and quality assurance.
conclusionAI and digital applications offer new care models and can help to increase efficiency. Challenges exist in terms of data quality, information technology infrastructure and the safe and responsible use of technologies. Future developments should be interdisciplinary.
Indexed as
Identifiers
40659882What 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.