Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy

An RF-based diagnostic model effectively identifies OME in AH children by integrating anatomical, functional, and inflammatory parameters, providing a clinically applicable tool for enhanced diagnostic accuracy and evidence-based management decisions.

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Publication Details

Journal
Frontiers in Pediatrics
Published
2025-06-19
DOI
https://doi.org/10.3389/fped.2025.1614495
Primary Topic
Obstructive Sleep Apnea Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy

Qiaoyi Xie, Xiaote Zhang, Guangyong Wu
Frontiers in Pediatrics
Obstructive Sleep Apnea Research
article

Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy

Qiaoyi Xie, Xiaote Zhang, Guangyong Wu
article en

Abstract

An RF-based diagnostic model effectively identifies OME in AH children by integrating anatomical, functional, and inflammatory parameters, providing a clinically applicable tool for enhanced diagnostic accuracy and evidence-based management decisions.

Frontiers in PediatricsVol. 13
Ningbo No. 2 Hospital (CN), Ningbo University Affiliated Hospital (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 81%
Obstructive Sleep Apnea Research
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