Olap Mining in Clinical Decision Support System for Medical Diagnosis

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Reddy Sony Krishna
Neelima Naralasetty, Jayalakshmi Gundabathina


Medical area produces increasingly voluminous amounts of electronic data which is more complicated for decision making. The developed clinical decision support system (CDSS) used a prototype On-Line Analytical Processing (OLAP) mining for medical diagnosis using advanced technologies such as On-Line Analytical Processing and Data Mining to deliver advanced capabilities by combining the strengths of both. This approach provides a rich acquaintance environment, not achievable by using OLAP alone or data mining alone. This work deals with CDSS using OLAP mining prototype to prepare diagnosis reports contains the proportion of patients’ sick and healthy on the whole medical data set. Using developed CDSS physicians and health care professionals obtains a decision on decisive symptom values that can be enumerated for further study on disease. These decisive symptom values and analysis reports of clinical support system are provided with better visualization results to the user that improves clinical environment.

Keywords:-Clinical decision support system,OLAP, decisive symptom,diabetes.


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