⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

February 20, 2024Acute and Critical CareOpen Access

Development of a deep learning model for predicting critical events in a pediatric intensive care unit

In Kyung Lee Bongjin Lee June Dong Park

View Full Paper

Ask AI

Bookmark

Share

Ask about this paper

Answers are grounded in this paper and cite their sources.

Ask your own question…

Abstract

Identifying critically ill patients at risk of cardiac arrest is important because it offers the opportunity for early intervention and increased survival. The aim of this study was to develop a deep learning model to predict critical events, such as cardiopulmonary resuscitation or mortality.

Discussion

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

Cite This Study

Lee et al. (2024) studied this question.

synapsesocial.com/papers/68e786f4b6db6435876f9604 https://doi.org/10.4266/acc.2023.01424

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:

1Development of a deep learning model that predicts critical events of pediatric patients admitted to general wards2024 · 4 citations
2Predictive Modelling of Critical Vital Signs in ICU Patients by Machine Learning: An Early Warning System for Improved Patient Outcomes2024 · 39 citations
3Predicting Cardiac Arrest in Children with Heart Disease: A Novel Machine Learning Algorithmcase-control · 2023 · 11 citations
4A Deep Learning Framework for Prediction of Cardiopulmonary Arrest2024 · 1 citations
5A Machine Learning Approach Using Statistical Models for Early Detection of Cardiac Arrest in Newborn Babies in the Cardiac Intensive Care Unit2025 · 1 citations

A MACHINE LEARNING APPROACH USING STATISTICAL MODELS FOR EARLY DETECTION2026
A Machine Learning Approach Using Statistical Models for Early Detection of Cardiac Arrest in Newborn Babies in the Cardiac Intensive Care Unit2023
Development and validation of a deep learning model to predict the survival of patients in ICU2022
Clinical characteristics and risk factors for intensive care unit admission and mortality in rapid response team-activated ward patients: a retrospective cohort study at a tertiary hospital in South KoreaAcute and Critical Care · 2026
The effects of intravenous glutamine supplementation in critically ill patients: a systematic review and meta-analysisAcute and Critical Care · 2026

More from Acute and Critical Care

More from Seoul National University Hospital

More from Seoul St. Mary's Hospital