DISEASE STATUS PREDICTION AND IDENTIFICATION
Keywords:
data mining; clinical decision support system; expert application; disease prediction; C4.5Abstract
Electronic Health Records (EHRs) are the main source of information for assessment, diagnosis, and
treatment of disease in clinical care. An EHR typically contains a patient’s historical health data, collected over
several years of patient care. This data includes both physician’s clinical notes written in unstructured text recording
their observations, assessments, and plans, as well as structured data such as ordered medications, vital signs
measurements, laboratory test results, and procedures conducted. The system takes input and helps the user to predict
the disease. The result for the same is provided. The proposed system assists doctor to predict disease correctly and the
prediction makes patients and medical insurance providers benefited. The use of EHRs are very limited when the
scenario in our country is taken into account. This can also benefit the physician since the patient history will be
readily available and in a structured format. Through the visits the results will be stored and a record will be
maintained. Thus, our system will enhance the usage of EHR to store data as well as to predict the disease accurately
and efficiently.
