Discovering Sequential Disease Patterns in Medical Databases Using FreeSpan Mining Approach

In this work we employ FreeSpan,
one of the sequential pattern mining methods, to
discover sequential disease patterns in sequential
database. For our study, we use a medical database
which was built as a transactional database. There
is a different representation data with sequential
database that will be used as an input for FreeSpan
method. Therefore, we build sequential database
from medical databases. The generated patterns
are used as knowledge to predict the sequential
disease. Therefore, the medical representative can
take preventive and curative actions more precise.
To make the sequential disease patterns easily to
understand, we visualize the pattern using graph.