An Ontology based Expert System for Diagnosis and Recommendation in Hemodialysis Patient
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Abstract
- This paper proposed the development of an ontology based expert system for diagnosis and recommendation in hemodialysis patients due to lack of expert dialysis nurses. Knowledge of the system is extracted from academic textbooks and tacit knowledge from expert dialysis nurses and is represented as If-Then Rules and Ontology. The knowledgebase of the system contains 89 rules, 52 concepts of drug ontology and 130 concepts of food ontology. The rule conditions are consisted of 26 patient’s blood test results and patient's medical treatment history. The system uses forward chaining to inference the diagnosis and recommendation for patients. The system was developed with PHP programming language and MySQL database is used for storing the knowledge and the data of the system. After 30 patient’s data were treated in this experiment, results found that the expert system can efficiently diagnosis and recommend patients with precision value of 96.89% and recall value of 95.39%, comparing with expert dialysis nurses’ answers.
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