ReviewFrontiers in pediatrics2019
Early Identification of Childhood Asthma: The Role of Informatics in an Era of Electronic Health Records.
Review in Frontiers in pediatrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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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
16 citing papers in PubMed.
- Effect of an electronic health record-integrated machine learning asthma risk marker on pediatrician prognostic accuracy during preschool age: a pilot randomized clinical trial.Scientific reports · 2026Trial
- Artificial intelligence-assisted clinical decision support for childhood asthma management: A randomized clinical trial.PloS one · 2021Trial
- A lifecycle governance and learning health system framework for trustworthy, generalizable, and sustainable human-ai partnership in clinical practice: Lessons from the asthma-guidance and prediction system (A-GPS).Journal of the National Medical Association · 2026Review
- Feasibility and acceptability of a passive digital marker for childhood asthma risk prognosis: a pilot cross-sectional study.Pilot and feasibility studies · 2026Article
- Application of a natural language processing algorithm to early asthma ascertainment for adults in the era of electronic health records.The journal of allergy and clinical immunology. Global · 2026Article
- Artificial intelligence biomarker detects high-risk childhood asthma subgroup for respiratory infections and exacerbations.The Journal of allergy and clinical immunology · 2025Article
- Intraoperative Bronchospasm and Future Asthma in Children: A Retrospective Matched Cohort Study.Paediatric anaesthesia · 2025Article
- External validation and update of the pediatric asthma risk score as a passive digital marker for childhood asthma using integrated electronic health records.EClinicalMedicine · 2025Article
- Association of delayed asthma diagnosis with asthma exacerbations in children.The journal of allergy and clinical immunology. Global · 2025Article
- Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report.BMC medical research methodology · 2023Article
- Validation of Diagnostic Coding for Asthma in an Electronic Health Record System in Hong Kong.Journal of asthma and allergy · 2023Article
- Risk, Mechanisms and Implications of Asthma-Associated Infectious and Inflammatory Multimorbidities (AIMs) among Individuals With Asthma: a Systematic Review and a Case Study.Allergy, asthma & immunology research · 2021Review
- Artificial intelligence approaches using natural language processing to advance EHR-based clinical research.The Journal of allergy and clinical immunology · 2020Review
- RoBERTa-Assisted Outcome Prediction in Ovarian Cancer Cytoreductive Surgery Using Operative Notes.Cancer control : journal of the Moffitt Cancer CenterArticle
- Biomarkers for selecting biologic therapies in asthma.Therapeutic advances in respiratory diseaseReview
- Correlation between the severity of asthma and computed tomography-based large airway structural changes among children under 3 years of age.Annals of thoracic medicineArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Emerging literature suggests that delayed identification of childhood asthma results in an increased risk of long-term and various morbidities compared to those with timely diagnosis and intervention, and yet this risk is still overlooked. Even when children and adolescents have a history of recurrent asthma-like symptoms and risk factors embedded in their medical records, this information is sometimes overlooked by clinicians at the point of care. Given the rapid adoption of electronic health record (EHR) systems, early identification of childhood asthma can be achieved utilizing (1) asthma ascertainment criteria leveraging relevant clinical information embedded in EHR and (2) innovative informatics approaches such as natural language processing (NLP) algorithms for asthma ascertainment criteria to enable such a strategy. In this review, we discuss literature relevant to this topic and introduce recently published informatics algorithms (criteria-based NLP) as a potential solution to address the current challenge of early identification of childhood asthma.
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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.