ReviewPediatric research2023
Artificial intelligence-based clinical decision support in pediatrics.
Review in Pediatric research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 4 of them syntheses that pooled it.
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
79 citing papers in PubMed, 4 syntheses or guidelines pooled it, 151 citations in OpenAlex.
- Artificial Intelligence for Diagnosis, Risk Stratification, and Prognosis of Neuroblastoma - A Systematic Review and Meta-Analysis.Current oncology reports · 2026Pooled it
- Leveraging ChatGPT to strengthen pediatric healthcare systems: a systematic review.European journal of pediatrics · 2025Pooled it
- Predictors of Health Care Practitioners' Intention to Use AI-Enabled Clinical Decision Support Systems: Meta-Analysis Based on the Unified Theory of Acceptance and Use of Technology.Journal of medical Internet research · 2024Pooled it
- Predictive Models to Assess Risk of Persistent Opioid Use, Opioid Use Disorder, and Overdose.Journal of addiction medicinePooled it
- Personalized Medicine in Pediatric Urology: From Diagnosis to Individualized Risk Assessment.Medical sciences (Basel, Switzerland) · 2026Review
- Large Language Model Decision Support for Cranial CT in Pediatric Head Trauma.Diagnostics (Basel, Switzerland) · 2026Article
- Emerging Applications of Artificial Intelligence in Pediatric Care.Indian journal of pediatrics · 2026Review
- Artificial intelligence and pediatric imaging data: ethical strategies for learning and collaboration.Pediatric radiology · 2026Review
- The role of artificial intelligence in paediatric abdominal imaging.Pediatric radiology · 2026Review
- Automated detection of periapical lesions in pediatric panoramic radiographs using YOLOv7: a retrospective internal validation study.BMC pediatrics · 2026Article
- Artificial intelligence assisted telemedicine, clinical decision support for anesthesia and critical care in intensive care units: a scoping review.BMC anesthesiology · 2026Article
- A Trusted AI-Driven Parent-Baby Companion App as a Perioperative Support Tool for Pediatric Surgical Practice.Cureus · 2026Article
- Harnessing artificial intelligence for pediatric health: Current trends and future opportunities.iScience · 2026Review
- "Hallucinations" of artificial intelligence tools misleading patients and families.Journal of family medicine and primary care · 2026Article
- Article
- Assessment of Generative AI Chatbots for Neonatal Diagnostic Reasoning: A Comparative Concordance and Diagnosis Acceptability Analysis.Indian journal of pediatrics · 2026Article
- Multi-criteria evaluation of clinical decision-making performance in spinal neurosurgery and physical therapy scenarios: A comparative analysis of artificial intelligence models.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Observational
- Auditor models to suppress poor artificial intelligence predictions can improve human-artificial intelligence collaborative performance.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Applications of artificial intelligence in pediatric general surgery: a systematic review.Translational pediatrics · 2026Review
- Recent Advances in AI and GenAI for Health Informatics.Healthcare (Basel, Switzerland) · 2026Review
19 more citing papers are in PubMed but not listed here.
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 at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Machine learning models may be integrated into clinical decision support (CDS) systems to identify children at risk of specific diagnoses or clinical deterioration to provide evidence-based recommendations. This use of artificial intelligence models in clinical decision support (AI-CDS) may have several advantages over traditional "rule-based" CDS models in pediatric care through increased model accuracy, with fewer false alerts and missed patients. AI-CDS tools must be appropriately developed, provide insight into the rationale behind decisions, be seamlessly integrated into care pathways, be intuitive to use, answer clinically relevant questions, respect the content expertise of the healthcare provider, and be scientifically sound. While numerous machine learning models have been reported in pediatric care, their integration into AI-CDS remains incompletely realized to date. Important challenges in the application of AI models in pediatric care include the relatively lower rates of clinically significant outcomes compared to adults, and the lack of sufficiently large datasets available necessary for the development of machine learning models. In this review article, we summarize key concepts related to AI-CDS, its current application to pediatric care, and its potential benefits and risks. IMPACT: The performance of clinical decision support may be enhanced by the utilization of machine learning-based algorithms to improve the predictive performance of underlying models. Artificial intelligence-based clinical decision support (AI-CDS) uses models that are experientially improved through training and are particularly well suited toward high-dimensional data. The application of AI-CDS toward pediatric care remains limited currently but represents an important area of future research.
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.