SEPSIS DIAGNOSIS SYSTEM using MACHINE LEARNING

  • M.Kiruthiga Devi, C.Divyabharathi , P.Haritha, Prakash Gunasekaran

Abstract

The timeliness of detection of a sepsis incidence in progress is a crucial factor in the outcome for the patient. Machine learning models built from data in electronic health records can be used as an effective tool for improving this timeliness, but so far, the potential for clinical implementations has been largely limited to studies in intensive care units[3]. This study will employ a richer data set that will expand the applicability of these models beyond intensive care units.

Published
2019-12-30