TOWARDS AN AUTOMATED NOSOCOMIAL INFECTION CASE REPORTING - Framework to Build a Computer-aided Detection of Nosocomial Infection

Jimison Iavindrasana, Gilles Cohen, Adrien Depeursinge, Henning Müeller, Rodolphe Meyer, Antoine Geissbuhler

2009

Abstract

The prevalence survey is a valid and realistic surveillance strategy for nosocomial infection surveillance but it is resource and labor-consuming. Querying the hospital data warehouse with a set of relevant features and applying a classification algorithm on the results can reduce the amount of cases to be evaluated by the infection control practitioners. The objective of this work is to provide a framework to build a nosocomial infection model with a set of pre-selected features with Fisher’s linear discriminant algorithm. Application of the methodology to two datasets provides promising results. It permits to predict respectively an average of 41.5% and 43.54% positive cases including respectively 65.37% and 82.56% true positive cases. The proposed framework can be applied to other classification algorithms, which are planned as future work.

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Paper Citation


in Harvard Style

Iavindrasana J., Cohen G., Depeursinge A., Müeller H., Meyer R. and Geissbuhler A. (2009). TOWARDS AN AUTOMATED NOSOCOMIAL INFECTION CASE REPORTING - Framework to Build a Computer-aided Detection of Nosocomial Infection . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2009) ISBN 978-989-8111-63-0, pages 317-322. DOI: 10.5220/0001553103170322


in Bibtex Style

@conference{healthinf09,
author={Jimison Iavindrasana and Gilles Cohen and Adrien Depeursinge and Henning Müeller and Rodolphe Meyer and Antoine Geissbuhler},
title={TOWARDS AN AUTOMATED NOSOCOMIAL INFECTION CASE REPORTING - Framework to Build a Computer-aided Detection of Nosocomial Infection },
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2009)},
year={2009},
pages={317-322},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001553103170322},
isbn={978-989-8111-63-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2009)
TI - TOWARDS AN AUTOMATED NOSOCOMIAL INFECTION CASE REPORTING - Framework to Build a Computer-aided Detection of Nosocomial Infection
SN - 978-989-8111-63-0
AU - Iavindrasana J.
AU - Cohen G.
AU - Depeursinge A.
AU - Müeller H.
AU - Meyer R.
AU - Geissbuhler A.
PY - 2009
SP - 317
EP - 322
DO - 10.5220/0001553103170322