EARLY IDENTIFICATION OF VENTILATOR ASSOCIATED PNEUMONIA USING MACHINE LEARNING TECHNIQUES: A PROSPECTIVE COHORT STUDY

Unité de recherche

INNOSUISSE

Numéro de projet

102.522.1 IP-ICT

Titre du projet

EARLY IDENTIFICATION OF VENTILATOR ASSOCIATED PNEUMONIA USING MACHINE LEARNING TECHNIQUES: A PROSPECTIVE COHORT STUDY

Titre du projet anglais

EARLY IDENTIFICATION OF VENTILATOR ASSOCIATED PNEUMONIA USING MACHINE LEARNING TECHNIQUES: A PROSPECTIVE COHORT STUDY

Textes relatifs à ce projet

	Allemand	Français	Italien	Anglais
Description succincte		-	-
Résumé des résultats (Abstract)		-	-

Catégorie	Texte
Description succincte (Allemand)	EARLY IDENTIFICATION OF VENTILATOR ASSOCIATED PNEUMONIA USING MACHINE LEARNING TECHNIQUES: A PROSPECTIVE COHORT STUDY
Description succincte (Anglais)	EARLY IDENTIFICATION OF VENTILATOR ASSOCIATED PNEUMONIA USING MACHINE LEARNING TECHNIQUES: A PROSPECTIVE COHORT STUDY
Résumé des résultats (Abstract) (Allemand)	VAP is burdened by increased morbidity and mortality. Due to lack of accurate diagnostic criteria we aim to develop different AI-algorithms using data from mechanical ventilators. VAP detection by accurate AI-algorithm has the potential to reduce morbidity, mortality, antibiotic overuse and costs.
Résumé des résultats (Abstract) (Anglais)	VAP is burdened by increased morbidity and mortality. Due to lack of accurate diagnostic criteria we aim to develop different AI-algorithms using data from mechanical ventilators. VAP detection by accurate AI-algorithm has the potential to reduce morbidity, mortality, antibiotic overuse and costs.