Data-mining-based detection of adverse drug events.
Stud Health Technol Inform
; 150: 552-6, 2009.
Article
em En
| MEDLINE
| ID: mdl-19745372
ABSTRACT
Every year adverse drug events (ADEs) are known to be responsible for 98,000 deaths in the USA. Classical methods rely on report statements, expert knowledge, and staff operated record review. One of our objectives, in the PSIP project framework, is to use data mining (e.g., decision trees) to electronically identify situations leading to risk of ADEs. 10,500 hospitalization records from Denmark and France were used. 500 rules were automatically obtained, which are currently being validated by experts. A decision support system to prevent ADEs is then to be developed. The article examines a decision tree and the rules in the field of vitamin K antagonists.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Armazenamento e Recuperação da Informação
/
Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Ano de publicação:
2009
Tipo de documento:
Article