Predicting Sepsis in the Intensive Care Unit (ICU) through Vital Signs using Support Vector Machine (SVM)

نویسندگان

چکیده

Background: As sepsis is one of the life-threatening diseases, predicting with high accuracy could help save lives. Methods: Efficiency and can be enhanced through optimal feature selection. In this work, a support vector machine model proposed to automatically predict patient’s risk based on physiological data collected from ICU. Results: The algorithm that uses extracted features has great impact prediction, which yields 0.73. Conclusion: Predicting accurately performed using main vital signs machine.

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ژورنال

عنوان ژورنال: The Open Bioinformatics Journal

سال: 2021

ISSN: ['1875-0362']

DOI: https://doi.org/10.2174/18750362021140100108