Intelligent management of epidemiologic data.
In the lifecycle of epidemiologic data three steps can be identified: production, interpretation and exploitation for decision. Computerized support can be precious, if not indispensable, at any of the three levels, therefore several epidemiologic data management systems were developed. In this paper we focus on intelligent management of epidemiologic data, where intelligence is needed in order to analyze trends or to compare observed with reference value and possibly detect abnormalities. After having outlined the problems involved in such a task, we show the features of ADAMS, a system realized to manage aggregated data and implemented in a personal computer environment.
Ferri
F
F
University of Rome, Italy.
Evoli
L M
LM
Pisanelli
D M
DM
Ricci
F L
FL
D001185:Artificial Intelligence; D003627:Data Interpretation, Statistical; D003628:Database Management Systems; D016208:Databases, Factual; D004812:Epidemiologic Methods; D008838:Microcomputers; D014584:User-Computer Interface