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 sepsis
2022
EMBC Proceedings
EMBC
Lombardi S.; Partanen P.; Bocchi L.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1285842
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