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Machine Learning for Urinary Tract Infection Prediction in Emergency Departments: An Explainable Approach

2025-12-18

Abstract excerpt

Urinary tract infections (UTIs) represent a substantial burden in emergency department (ED) settings, where diagnostic delays and the limitations of traditional clinical assessments often result in suboptimal treatment decisions. This study develops an interpretable machine learning framework to enhance real-time UTI prediction accuracy. We analyzed a retrospective dataset of 80,387 ED patient encounters from four...

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Literature Corpus work
8c76a08a-f2c2-59f5-abb0-e37ec0275b94
DOI
10.64898/2025.12.13.25342059
Open publication

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Machine Learning for Urinary Tract Infection Prediction in Emergency Departments: An Explainable ApproachDOI 10.64898/2025.12.13.25342059
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