A Hybrid Model for Enhanced Medical Intelligence Process using Ontology Based and Virtual Data Integration Technique - EC, Asogwa; VE, Ejiofor; BC, Amanze; AO, Agbakwuru; TS, Belonwu (International Journal of Computer Sciences and Engineering, 2022)
The business model developed focused on expert system for health sector that uses intelligent agent to guide doctors in accurately carrying out disease control procedures. The objective of the paper is to create ontology-based data integration (OBDI) system process model that can uses intelligent agent to guide doctors in accurately carrying out disease control procedures. The system developed used to manage a disease registry that consists of the concepts of the domain, the attributes characterizing each disease, the different symptoms, and treatments. A model for enhanced medical intelligence process using ontology based technique developed. The design provided for a database system for storing medical records, software for enhanced Medical Intelligence Process that would be more user-friendly, flexible, adaptive, intelligent, agile and automatic in integrating and analyzing medical data thereby helping medical practitioners at various levels to make realistic intelligent and real-time decision on critical health issues. Object Oriented Analysis and Design Methodology (OOADM) adopted in the design of the system. The system achieved integration of various patients medical records from different hospitals using ontology based and virtual data integration technique that will allow clinic data of one patient collected together to form a combinational resource, and could be accessed by physician if authority is assigned to the physician. Ontology-based data integration technique for disease control procedure achieved 95% accuracy in predicting the disease control procedure.