loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Rui Veloso 1 ; Filipe Portela 1 ; Manuel Filipe Santos 1 ; Álvaro Silva 2 ; Fernando Rua 2 ; António Abelha 1 and José Machado 1

Affiliations: 1 University of Minho, Portugal ; 2 Hospital Santo António, Portugal

Keyword(s): Antibiotics, Therapies, Infections, Bacteria, Intensive Care Units, Heuristics, Artificial Intelligence, INTCare, Decision Support.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Industrial Applications of AI ; Knowledge-Based Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems

Abstract: Nowadays antibiotic prescription is object of study in many countries. The rate of prescription varies from country to country, without being found the reasons that justify those variations. In intensive care units the number of new infections rising each day is caused by multiple factors like inpatient length of stay, low defences of the body, chirurgical infections, among others. In order to complement the support of the decision process about which should be the most efficient antibiotic it was developed a heuristic based in domain knowledge extracted from biomedical experts. This algorithm is implemented by intelligent agents. When an alert appear on the presence of a new infection, an agent collects the microbiological results for cultures, it permits to identify the bacteria, then using the rules it searches for a role of antibiotics that can be administered to the patient, based on past results. At the end the agent presents to physicians the top-five sets and the success perc entage of each antibiotic. This paper presents the approach proposed and a test with a particular bacterium using real data provided by an Intensive Care Unit. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.119.248.214

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Veloso, R.; Portela, F.; Filipe Santos, M.; Silva, Á.; Rua, F.; Abelha, A. and Machado, J. (2015). Using Domain Knowledge to Improve Intelligent Decision Support in Intensive Medicine - A Study of Bacteriological Infections . In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-074-1; ISSN 2184-433X, SciTePress, pages 582-587. DOI: 10.5220/0005286405820587

@conference{icaart15,
author={Rui Veloso. and Filipe Portela. and Manuel {Filipe Santos}. and Álvaro Silva. and Fernando Rua. and António Abelha. and José Machado.},
title={Using Domain Knowledge to Improve Intelligent Decision Support in Intensive Medicine - A Study of Bacteriological Infections },
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2015},
pages={582-587},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005286405820587},
isbn={978-989-758-074-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Using Domain Knowledge to Improve Intelligent Decision Support in Intensive Medicine - A Study of Bacteriological Infections
SN - 978-989-758-074-1
IS - 2184-433X
AU - Veloso, R.
AU - Portela, F.
AU - Filipe Santos, M.
AU - Silva, Á.
AU - Rua, F.
AU - Abelha, A.
AU - Machado, J.
PY - 2015
SP - 582
EP - 587
DO - 10.5220/0005286405820587
PB - SciTePress