Evidence-based Guideline System is providing an effective process to treating a patient. it totally work on the "Clinical Evidences" which are created by applying data mining techniques on collected data about particular disease and the rule generated by data mining process is further analyze by various medical field experts. These verified rules become the "Clinical Evidence" then these evidences are used to predict patient disease and provide Clinical guideline related to particular "Clinical Evidence" to patient if Patient medical parameters of disease matching with medical parameter of "Clinical Evidence". In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must necessary. In this research Data warehousing and data mining support the creation of the Evidence-based rules by providing a platform and tools for knowledge discovery. Large amounts of data can be analyzed to confirm known or discover unknown trends and correlations in data. In this Dissertation, We will predict Thyroid Disease and giving appropriate clinical guidelines to Doctor to diagnose their patient according to Thyroid "Clinical Evidences". This dissertation is intended to provide a roadmap for achieving sustainable healthcare decision support system based on data warehouses and data mining, facilitating evidence-based medicine that which are used to diagnose patients.

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Clinical Evidence Ebm Ebgs Thyroid K-mean And K-medoid