Clinical Profile Identification of Indigenous Infants With Bronchiolitis Through Using Unsupervised Feature Extraction and Clustering

Using UFEAs and clustering, we reduced dataset dimensionality, effectively identifying six unique, clinically significant risk profiles in Indigenous infants.

Authors

Hongqi Niu (ORCID: https://orcid.org/0000-0002-9848-9574)
Anne B. Chang (ORCID: https://orcid.org/0000-0002-1331-3706)
Gabrielle Britt McCallum (ORCID: https://orcid.org/0000-0002-0210-1468)
Sami Azam
Khalid Khan

Institutions

Charles Darwin University (AU)
Menzies School of Health Research (AU)
Children’s Health Queensland Hospital and Health Service (AU)
Children's Health Queensland Hospital and Health Service (AU)

Publication Details

Journal: Pediatric Pulmonology
Published: 2026-01-01
DOI: https://doi.org/10.1002/ppul.71449
Primary Topic: Respiratory viral infections research
Type: article
Field-Weighted Citation Impact: 0.00

Funders

Australian Government
National Health and Medical Research Council

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article

Clinical Profile Identification of Indigenous Infants With Bronchiolitis Through Using Unsupervised Feature Extraction and Clustering

Hongqi Niu, Anne B. Chang, Gabrielle Britt McCallum, Sami Azam et al.

Jan 1, 2026

Pediatric Pulmonology

Respiratory viral infections research

article

Clinical Profile Identification of Indigenous Infants With Bronchiolitis Through Using Unsupervised Feature Extraction and Clustering

Hongqi Niu, Anne B. Chang, Gabrielle Britt McCallum, Sami Azam, Khalid Khan

January 1, 2026article en

Abstract

Using UFEAs and clustering, we reduced dataset dimensionality, effectively identifying six unique, clinically significant risk profiles in Indigenous infants.

Pediatric PulmonologyVol. 61(1)

Charles Darwin University (AU), Menzies School of Health Research (AU), Children’s Health Queensland Hospital and Health Service (AU), Children's Health Queensland Hospital and Health Service (AU)

Australian Government, National Health and Medical Research Council

Good health and well-being

Openalex Percentile: Top 97%

Respiratory viral infections research

DOI Open Access PDF OpenAlex

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