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Enhancing the clinical decision making of sepsis detection: a machine learning approach to early diagnosis
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Resumo(s)
Sepsis is a perilous, life-threatening illness and is a leading cause of death in the world; with
an annual death toll of 6 million people worldwide (Reyna et al., 2019). The syndromic nature
of the condition is convoluted and almost indistinguishable from uncomplicated infections.
Sepsis requires immediate admission to an intensive care unit, and every hour of delay was
associated with an absolute mortality rate of 0.3% for sepsis and 1.8% for sepsis shock. To
further current endeavours in early sepsis detection, this study offers a machine learning model
that predicts sepsis 12 hours before the onset time of sepsis-3 clinical criteria; the current norm
for diagnosing sepsis.
Descrição
Palavras-chave
Machine learning Healthcare Artificial intelligence Sepsis Early diagnosis