Master of Science in Computer Science
Department of Computer Science
School of Mathematics and Computer Science (SMCS)
Date of Submission
Dr. Farhan Ahmed Siddiqui, Visiting Faculty, Department of Computer Science
This paper presents a clinical decision support system app that leverages the power of the Semantic Web to enhance healthcare decision-making processes. By harnessing semantic technologies, the system enables the integration, representation, and reasoning of healthcare knowledge from diverse sources. This system utilizes ontologies, such as SNOMED CT, LOINC, and SPHN, to ensure standardization and interoperability of medical data. The app incorporates a graph database, Neo4j, to store and query structured medical information. Through the use of the Cypher query language, the system performs advanced inferencing and reasoning to derive meaningful insights and support clinical decision-making. Additionally, a custom dashboard, provides intuitive visualization and monitoring of patient data, facilitating data-driven insights and improved patient care. The app showcases the potential of the Semantic Web in the clinical domain, enabling clinicians to access comprehensive and interconnected medical knowledge for making informed decisions.
Khan, Soha. "A semantic web-based clinical decision support system." Unpublished graduate research project. Institute of Business Administration. 2023. https://ir.iba.edu.pk/research-projects-mscs/27
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