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Published in:
2010 | OriginalPaper | Chapter
Modeling and Automation of Diagnosis and Treatment of Diabetes
Authors : Abhirami Baskaran, Dhivya Karthikeyan, Anusha T. Swamy
Published in: Simulated Evolution and Learning
Publisher: Springer Berlin Heidelberg
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The present work aims at designing and implementing an automated decision making system for the treatment of diabetes. The automated medical tool has been equipped to handle the decisions regarding the care plan of the patient and also helps in diagnosis. It takes in essential parameters like glucose, cholesterol, blood pressure and devises a care plan for the patient. Fuzzy logic was used to implement the medical decision support system. A knowledge base for diabetes containing the essential concepts, treatment algorithms was created. The fuzzy logic based system used the knowledge base for constructing the collection of rules. The essential parameters from the patient database were provided as input and the decisions like the type of diabetes, diet plans, medication etc were recorded. The tool also takes the decisions and the parameters that led to the decisions to build an optimal care pathway for the patient.