DEVELOPMENT OF A HEALTHCARE EXPERT SYSTEM CASE STUDY: ELIZADE UNIVERSITY LIBRARY
Abstract
ABSTRACT
In response to the growing complexity of clinical decision-making in Nigeria’s primary healthcare settings, this project presents the development of a rule-based HES (Healthcare Expert System). The system is designed to assist healthcare professionals by providing diagnostic suggestions based on structured symptom inputs. Utilizing real-world patient data from Elizade University Clinic, the system employs an expert system architecture that integrates a curated knowledge base, feature selection, and an inference engine grounded in IF-THEN logic. A total of 62 common diagnoses were mapped to associated symptom sets, forming the foundation for rule-based decision-making. The system interface enables users to input symptoms and retrieve ranked diagnostic outcomes with confidence scores, offering speed, accuracy, and interpretability in environments with limited diagnostic infrastructure. Evaluation of the system showed high performance in diagnosing frequent tropical diseases such as malaria and upper respiratory tract infections. The HES (Healthcare Expert System) demonstrates significant potential to reduce diagnostic delays, enhance decision consistency, and support overburdened healthcare workers, particularly in rural and resource-constrained settings. Recommendations for future enhancements include fuzzy symptom matching, severity indicators, and integration of patient-specific data for personalized care.
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