Project title
Ontology Chatbot
Project aim
Aimed at addressing the challenge of accurately identifying diseases through text input, the project leverages the synergy between advanced computational algorithms and medical ontologies to create a user-friendly and efficient diagnostic tool.
Project outline
This Project presents the development and evaluation of an innovative approach to medical diagnosis through the integration of a chatbot with an ontology-based rule-expert system.
Utilizing the World Wide Web Consortium (W3C) Web Ontology Language (OWL) for knowledge representation and Python for backend development, the system combines the depth of medical knowledge with the accessibility of a chat interface.
The methodology encompasses the de- sign of a disease-symptom ontology, the implementation of a rule-based expert system employing backward chaining logic, and the development of a chatbot interface for symptom input and disease diagnosis communication.
Evaluation through simulated scenarios and test cases demonstrates the system’s potential to enhance disease diagnosis accuracy, providing users with reliable health in- formation.
The project identifies areas for future improvement, including the expansion of the disease-symptom ontology and the incorporation of multilingual support to broaden user accessibility.
The successful implementation of this project underscores the vital role of integrating ontology-based expert systems with chatbot technology in transforming healthcare diagnostics and offers a promising direction for future research in digital health solutions.