Intelligent Medical Cases Creation Using Medical Events

Abstract

The patient record exist in many forms and in the
different location. This record fails to gain an overall picture
of the patients health condition. The medical cases creation
system delivers accessible and accurate information of a patient
to health-care providers. This system will be able to retrieve the
complete medical background of the patient with a significant
advantage in treatment and diagnosis by imputing missing
attribute values and removing noise present in the patient record.
The fundamental function of medical cases is to record, monitor,
retrieve, analyze and predict all event and cases which are
an encounter between patient and the health-care system. The
purpose of the dissertation is to capture medical knowledge by
a computer which can aid doctors to determine a diagnosis.
The proposed framework is based on clustering technique and
imputation measure. Clustering techniques help in matching
particular pattern among patients attributes present in records.
We then focus on imputation measure which is used to fix
the missing attribute values present in the medical records and
finally, the multiple sets of results are combined to yield a single
inference.