Sepsis is one of the most frequent causes of death in Intensive Care Units, and its prognosis greatly depend on timeliness of diagnosis. MIMIC-III database is a frequent source of data for developing method for automatic sepsis detection. However, the heterogeneity of data jeopardize the feasibility of the task. In this work we propose a selection strategy for generating high quality data suitable for training a sepsis detection system based on the utilization of only plethysmographic data. Clinical relevance A system for detecting sepsis based only on PPG may be potentially at virtually no cost in any case clinicians suspect the possibility of developing sepsis
Detecting sepsis from photoplethysmography: strategies for dataset preparation / Lombardi S.; Partanen P.; Bocchi L.. - ELETTRONICO. - 2022-July:(2022), pp. 2286-2289. (Intervento presentato al convegno EMBC) [10.1109/EMBC48229.2022.9871973].
Detecting sepsis from photoplethysmography: strategies for dataset preparation
Lombardi S.;Bocchi L.
2022
Abstract
Sepsis is one of the most frequent causes of death in Intensive Care Units, and its prognosis greatly depend on timeliness of diagnosis. MIMIC-III database is a frequent source of data for developing method for automatic sepsis detection. However, the heterogeneity of data jeopardize the feasibility of the task. In this work we propose a selection strategy for generating high quality data suitable for training a sepsis detection system based on the utilization of only plethysmographic data. Clinical relevance A system for detecting sepsis based only on PPG may be potentially at virtually no cost in any case clinicians suspect the possibility of developing sepsisI documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.