Using Machine Learning to Predict Bacteremia in Febrile Children Presented to the Emergency Department.
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ABSTRACT:
SUBMITTER: Tsai CM
PROVIDER: S-EPMC7277905 | biostudies-literature | 2020 May
REPOSITORIES: biostudies-literature
Publications
Using Machine Learning to Predict Bacteremia in Febrile Children Presented to the Emergency Department.
Tsai Chih-Min CM Lin Chun-Hung Richard CR Zhang Huan H Chiu I-Min IM Cheng Chi-Yung CY Yu Hong-Ren HR Huang Ying-Hsien YH
Diagnostics (Basel, Switzerland) 20200515 5
Blood culture is frequently used to detect bacteremia in febrile children. However, a high rate of negative or false-positive blood culture results is common at the pediatric emergency department (PED). The aim of this study was to use machine learning to build a model that could predict bacteremia in febrile children. We conducted a retrospective case-control study of febrile children who presented to the PED from 2008 to 2015. We adopted machine learning methods and cost-sensitive learning to ...[more]
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