⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

November 24, 2025Critical Care ExplorationsOpen Access

Fast, Accurate Assignment of Clinical Diagnoses From Patient Notes by a Large Language Model: Critical Pediatric Pneumonia as a Use Case

Blake Martin Marisa Payan Jaime LaVelle Peter E. DeWitt Seth Russell James Mitchell Sara J Deakyne Davies Tellen D Bennett

View Full Paper

Ask AI

Bookmark

Share

Key Points

GPT-4o accurately classified 94.8% of pediatric encounters for bacterial pneumonia.
A total of 10,081 clinical notes from 3,317 PICU admissions were analyzed within 5 minutes.
Adjudication analysis showed a 71.8% match rate with a blinded attending physician's review of charts.
Automating the diagnosis process could enhance efficiency in managing pediatric patients with pneumonia.

No abstract yet

We only have this paper's title and publication details.

Read it at the source→

Ask about this paper

Answers are grounded in this paper and cite their sources.

Ask your own question…

Implication

Retrospective cohort study demonstrates accurate diagnosis of bacterial pneumonia in PICU, indicating potential to automate chart review.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Martin et al. (2025) studied this question.

synapsesocial.com/papers/6928f113a65b730b9ea79f3e https://doi.org/10.1097/cce.0000000000001350

View Full Paper

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Fast, Accurate Assignment of Clinical Diagnoses From Patient Notes by a Large Language Model: Critical Pediatric Pneumonia as a Use Case2025
2Diagnostic Accuracy of a Large Language Model (ChatGPT-4) for Patients Admitted to a Community Hospital Medical Intensive Care Unit: A Retrospective Case Study2025 · 3 citations
3Comparing the Quality of Domain-Specific Versus General Language Models for Artificial Intelligence-Generated Differential Diagnoses in PICU Patients*2024 · 19 citations
4Benchmarking Multimodal Large Language Models for Binary Classification of Pediatric Chest X-Rays: A Comparative Evaluation Using a Public Pneumonia Dataset2025
5P-2001. Integrating a host biomarker and a large language model for diagnosis of lower respiratory tract infectionCohort Study · 2026

Large Language Models Improve Coding Accuracy and Reimbursement in a Neonatal Intensive Care Unit2025
Diagnostic Accuracy of a Custom Large Language Model on Rare Pediatric Disease Case Reports2024
Evaluation of large language models as a diagnostic aid for complex medical cases2024
From Framework to Toolkit: Practical Guidance for Using the PrOcess Evaluation of Trials In Critical care (POETIC) FrameworkCritical Care Explorations · 2026
Characteristics and Outcomes of Patients Referred but Declined for ICU Admission in a Resource-Limited Setting in South AfricaCritical Care Explorations · 2026

More from Critical Care Explorations

More from University of Colorado Denver

More from Children's Hospital Colorado