Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/36734

TitleUsing domain knowledge to improve intelligent decision support in intensive medicine - a study of bacteriological infections
Author(s)Machado, José Manuel
Abelha, António
Rua, Fernando
Silva, Álvaro
Santos, Manuel Filipe
Portela, Filipe
Veloso, Rui
KeywordsAntibiotics
Artificial intelligence
Bacteria
Decision support
Heuristics
Infections
Intcare
Intensive care units
Therapies
Issue date2015
PublisherSCITEPRESS
Abstract(s)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 percentage 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.
TypeConference paper
URIhttp://hdl.handle.net/1822/36734
ISBN9789897580741
DOI10.5220/0005286405820587
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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