A scoping review of machine learning for sepsis prediction- feature engineering strategies and model performance: a step towards explainability
Sherali Bomrah,
Mohy Uddin,
Umashankar Upadhyay
et al.
Abstract:Background
Sepsis, an acute and potentially fatal systemic response to infection, significantly impacts global health by affecting millions annually. Prompt identification of sepsis is vital, as treatment delays lead to increased fatalities through progressive organ dysfunction. While recent studies have delved into leveraging Machine Learning (ML) for predicting sepsis, focusing on aspects such as prognosis, diagnosis, and clinical application, there remains a notable deficiency in the discour… Show more
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