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Using Self Organizing Maps to Compare Sepsis Patients from the Neonatal and Adult Intensive Care Unit
Benjamin Goddard1, Jonathan Chang1, Indra Neil Sarkar1
1Center for Biomedical Informatics, Brown University, Providence, RI USA.
Abstract:
Neonatal sepsis, a blood infection occurring in infants younger than 90 days old, represents a significant source of mortality and morbidity among infants.1 Mortality rates increase with postnatal age and can be as high as 52% (36% in newborns aged 8-14 days and 52% in those aged 15-28 days).2 While sepsis in adults has a generally accepted definition, the definition for clinical diagnosis in infants is less well defined. Using the Medical Information Mart for Intensive Care database (MIMIC-III), patient diagnoses and microbiology results records were processed with an artificial neural network trained using unsupervised learning known as a self-organizing map (SOM). The results of this feasibility study suggest a low degree of overlap between the presentation of sepsis in neonate and adult intensive care unit populations. As a consequence, it supports the need for dedicated research in neonatal sepsis, which may manifest differently than adult sepsis.
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