ReviewPediatric nephrology (Berlin, Germany)2026
AI-powered insights in pediatric nephrology: current applications and future opportunities.
Review in Pediatric nephrology (Berlin, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed.
- Artificial intelligence in pediatric nephrology: current applications and emerging frameworks for evidence generation.Pediatric nephrology (Berlin, Germany) · 2026Review
- Prediction of pediatric lower urinary tract dysfunction using uroflowmetry data and machine learning with explainable AI techniques.International urology and nephrology · 2026Article
- Prenatal body fluid analysis in the evaluation of CAKUT.Pediatric nephrology (Berlin, Germany) · 2026Article
- Evaluating the Performance of AI Large Language Models in Detecting Pediatric Medication Errors Across Languages: A Comparative Study.Journal of clinical medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is rapidly emerging as a transformative force in pediatric nephrology, enabling improvements in diagnostic accuracy, therapeutic precision, and operational workflows. By integrating diverse datasets-including patient histories, genomics, imaging, and longitudinal clinical records-AI-driven tools can detect subtle kidney anomalies, predict acute kidney injury, and forecast disease progression. Deep learning models, for instance, have demonstrated the potential to enhance ultrasound interpretations, refine kidney biopsy assessments, and streamline pathology evaluations. Coupled with robust decision support systems, these innovations also optimize medication dosing and dialysis regimens, ultimately improving patient outcomes. AI-powered chatbots hold promise for improving patient engagement and adherence, while AI-assisted documentation solutions offer relief from administrative burdens, mitigating physician burnout. However, ethical and practical challenges remain. Healthcare professionals must receive adequate training to harness AI's capabilities, ensuring that such technologies bolster rather than erode the vital doctor-patient relationship. Safeguarding data privacy, minimizing algorithmic bias, and establishing standardized regulatory frameworks are critical for safe deployment. Beyond clinical care, AI can accelerate pediatric nephrology research by identifying biomarkers, enabling more precise patient recruitment, and uncovering novel therapeutic targets. As these tools evolve, interdisciplinary collaborations and ongoing oversight will be key to integrating AI responsibly. Harnessing AI's vast potential could revolutionize pediatric nephrology, championing a future of individualized, proactive, and empathetic care for children with kidney diseases. Through strategic collaboration and transparent development, these advanced technologies promise to minimize disparities, foster innovation, and sustain compassionate patient-centered care, shaping a new horizon in pediatric nephrology research and practice.
Indexed as
Identifiers
What Socratic 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 Socratic graph.