ReviewEuropean journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie2026
Explainable AI: Ethical Frameworks, Bias, and the Necessity for Benchmarks.
Review in European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie, 2026. 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.
- Artificial intelligence, equity, and pediatric neurodevelopmental disorders: A scoping review of clinical practice applications.Pediatric investigation · 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
3 authors.
Funding
Abstract
Artificial intelligence (AI) is increasingly integrated into pediatric healthcare, offering opportunities to improve diagnostic accuracy and clinical decision-making. However, the complexity and opacity of many AI models raise concerns about trust, transparency, and safety, especially in vulnerable pediatric populations. Explainable AI (XAI) aims to make AI-driven decisions more interpretable and accountable. This review outlines the role of XAI in pediatric surgery, emphasizing challenges related to bias, the importance of ethical frameworks, and the need for standardized benchmarks. Addressing these aspects is essential to developing fair, safe, and effective AI applications for children. Finally, we provide recommendations for future research and implementation to guide the development of robust and ethically sound XAI solutions.
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.