Functional dependencies (FD s) typically represent associations over facts stored by a
database, such as “patients with the same symptom get the same therapy.” In more recent …

Clinical databases collect large volume of data. Relationships and patterns within these data
could provide new medical knowledge. Temporal data mining has as major scope the …

Approximate functional dependencies, even with suitable temporal extensions, have been
recently proposed as a methodological tool for mining clinical data. It allows healthcare …

Temporal functional dependencies add valid time to classical functional dependencies in
order to express data integrity constraints over the flow of time. If the temporal dimension …

In this paper, we propose a methodology for deriving a new kind of approximate temporal
functional dependencies, called Approximate Predictive Functional Dependencies (APFDs) …

Functional dependencies (FD) model constraints over databases like" employees with the
same role get the same salary". Some extensions have been introduced to represent …

Functional dependencies (FD s) allow us to represent database constraints, corresponding
to requirements as “patients having the same symptoms undergo the same medical tests.” …

In this paper, we propose a methodology for deriving a new kind of approximate temporal
functional dependencies, called Approximate Predictive Functional Dependencies (APFDs) …

Database constraints, such as" patients with the same symptoms get the same therapies",
may be modeled by means of functional dependencies (FD). They have been extended to …

Clinical databases collect large volumes of information. Relationships and patterns within
these data could provide new medical knowledge. Data mining has as major objective the …