Evaluation of the Need for Intensive Care in Children With Pneumonia: Machine Learning Approach.

ABSTRACT:

Background

Timely decision-making regarding intensive care unit (ICU) admission for children with pneumonia is crucial for a better prognosis. Despite attempts to establish a guideline or triage system for evaluating ICU care needs, no clinically applicable paradigm is available.

Objective

The aim of this study was to develop machine learning (ML) algorithms to predict ICU care needs for pediatric pneumonia patients within 24 hours of admission, evaluate their performance, and identify clinical indices for making decisions for pediatric pneumonia patients.

Methods

Pneumonia patients admitted to National Taiwan University Hospital from January 2010 to December 2019 aged under 18 years were enrolled. Their underlying diseases, clinical manifestations, and laboratory dat

SUBMITTER: Liu YC 

PROVIDER: S-EPMC8832265 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature