ReviewBundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz2025
[Artificial intelligence under scrutiny: requirements, quality criteria, and testing tools for medical applications].
Review in Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 2025. 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of artificial intelligence (AI) in medicine has great potential to improve quality and efficiency. At the same time, its use is associated with risks. In order to prevent harm, experts from research and politics are developing requirements, testing tools, and guidelines to identify and control these risks.This article first describes the requirements for AI in medicine. It then follows with a presentation of how concrete quality criteria and testing tools can be derived from those requirements. A deeper demonstration of "explainability" as a key criterion is presented as an example. A testing framework for the use of AI in medicine is also presented. Finally, the article provides an outlook on standardization of quality criteria.The development of AI, especially in medicine, is progressing quickly. Suitable testing procedures can help to minimize risks and strengthen trust in the technology. However, for the successful implementation of such testing procedures, continuous research efforts are necessary.
Indexed as
Identifiers
What 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.