Leveraging Machine Learning for Pediatric Appendicitis Diagnosis: A Retrospective Study Integrating Clinical, Laboratory, and Imaging Data

Leveraging Machine Learning for Pediatric Appendicitis Diagnosis: A Retrospective Study Integrating Clinical, Laboratory, and Imaging Data

ABSTRACT Background and Aims Appendicitis is the most common surgical emergency in pediatric patients, requiring timely diagnosis to prevent complications. This study introduces an innovative approach by integrating clinical, laboratory, and imaging features with advanced machine‐learning techniques...

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Bibliographic Details
Main Authors: Mahdi Navaei, Zohre Doogchi, Fatemeh Gholami, Moein Kermanizadeh Tavakoli
Format: Article
Language:English
Published: Wiley 2025-04-01
Series:Health Science Reports
Subjects:
abdominal pain
clinical practice
decision trees
diagnostic accuracy
emergency room
ensemble methods
Online Access:https://doi.org/10.1002/hsr2.70756
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https://doi.org/10.1002/hsr2.70756

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