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

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Research unit

INNOSUISSE

Project number

102.522.1 IP-ICT

Project title

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

Texts for this project

	German	French	Italian	English
Short description		-	-
Abstract		-	-

Inserted texts

Category	Text
Short description (German)	EARLY IDENTIFICATION OF VENTILATOR ASSOCIATED PNEUMONIA USING MACHINE LEARNING TECHNIQUES: A PROSPECTIVE COHORT STUDY
Short description (English)	EARLY IDENTIFICATION OF VENTILATOR ASSOCIATED PNEUMONIA USING MACHINE LEARNING TECHNIQUES: A PROSPECTIVE COHORT STUDY
Abstract (German)	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.
Abstract (English)	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.