ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2020
Natural Language Processing and Machine Learning to Enable Clinical Decision Support for Treatment of Pediatric Pneumonia.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Pediatric Predictive Artificial Intelligence Implemented in Clinical Practice from 2010 to 2021: A Systematic Review.Applied clinical informatics · 2025Pooled it
- Prognostic clinical decision support for pneumonia in the emergency department: A randomized trial.Journal of hospital medicine · 2024Trial
- User-Centered Design and Implementation of an Interoperable FHIR Application for Pediatric Pneumonia Prognostication in a Randomized Trial.Applied clinical informatics · 2024Trial
- Antibiotic clinical decision support for pneumonia in the ED: A randomized trial.Journal of hospital medicine · 2023Trial
- Personalized decision-making through AI solutions in pediatric emergency medicine: Focusing on febrile children.PLOS digital health · 2025Review
- Predicting Escalation of Care for Childhood Pneumonia Using Machine Learning: Retrospective Analysis and Model Development.JMIRx med · 2025Article
- Let's ask the patient: disease prediction based on patients' symptom descriptions in free text.Rheumatology advances in practice · 2025Article
- Prediction of intra-abdominal injury using natural language processing of electronic medical record data.Surgery · 2024Observational
- The predictive value of PCT, SP-D and 8-iso-PGF2 α for the development of severe pneumonia in children.African health sciences · 2024Article
- Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults.JMIR medical informatics · 2023Article
- Combining text mining with clinical decision support in clinical practice: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- The development of a novel natural language processing tool to identify pediatric chest radiograph reports with pneumonia.Frontiers in digital health · 2023Article
- Artificial intelligence-based clinical decision support in pediatrics.Pediatric research · 2023Review
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 at 1 institution in 1 country.
Funding
Abstract
Pneumonia is the most frequent cause of infectious disease-related deaths in children worldwide. Clinical decision support (CDS) applications can guide appropriate treatment, but the system must first recognize the appropriate diagnosis. To enable CDS for pediatric pneumonia, we developed an algorithm integrating natural language processing (NLP) and random forest classifiers to identify potential pediatric pneumonia from radiology reports. We deployed the algorithm in the EHR of a large children's hospital using real-time NLP. We describe the development and deployment of the algorithm, and evaluate our approach using 9-months of data gathered while the system was in use. Our model, trained on individual radiology reports, had an AUC of 0.954. The intervention, evaluated on patient encounters that could include multiple radiology reports, achieved a sensitivity, specificity, and positive predictive value of0.899, 0.949, and 0.781, respectively.
Indexed as
Identifiers
33936489PMC8075487W3158982765What 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.