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Clinical Decision Support System (CDSS) has become the ultimate point of care for healthcare sectors to assist the public in terms of Medical care. Through this research work, we propose the design and development of a Web-based Clinical Decision Support System (We-CDSS) using the Django framework with an aim to make CDSS accessible for both common people and clinicians on computers and mobile devices that integrates Predictive Analytics involving the LWGMK-NN algorithm for predicting Coronary Artery Disease, and Prescriptive Analytics involving prescription rules. The proposed research work consists of three phases. The first phase presents the design and development of a web-based CDSS outlook using the Django framework. The second and final phase embeds Predictive Analytics and Prescriptive Analytics into the We-CDSS to manage the functionalities of predictive decisions, and the functionalities of prescriptive processes that evaluate the predictive results and recommends personalized lifestyle suggestions to reduce the risk of coronary artery disease.

Design and Development of We-CDSS Using Django Framework: Conducing Predictive and Prescriptive Analytics for Coronary Artery Disease