WITHDRAWN: Semantic Web-based critical Healthcare system using Bayesian networks

Abstract

In this paper, a Semantic Web-based Critical Healthcare (SWCH) system is designed for early diagnosis and treatment of critical diseases which include Heart attack, Stroke, Cancer, Kidney failure and Brain tumour. It consists of knowledge Extraction anddiagnosis & disease prediction modules. In Knowledge extraction module, medical data from various sources is gathered. Based on this knowledge base, a medical Ontology model with Bayesian networks is developed which provides the diagnosis of whether the patient has the potential to have that critical disease. The domain experts have made an ontology rubrics about every sickness for ontology improvement in Diagnosis & disease prediction module. The fitness condition of a patientregarding the sickness is resolute using the suggested ontology samplethatreverts a group of health-related data. We have applied the suggested SWCH by relating web ontology language (OWL) and Semantic Web Rule Language (SWRL) centred on diverse classes associated with numeroussicknesses to acquire a knowledge-based demonstration. The presentation is assessed regarding the metrics such as Accuracy, sensitivity and specificity. Experimental results have shown that the accuracy of heart attack is 98%, brain tumour 96%, stroke 94% and kidney failure 94.5% The sensitivity of heart attack is 98%, brain tumour 97.4, stroke 96.4 and kidney failure 95.7% The specificity of heart attack is 98%, brain tumour 97.4, stroke 96.4 and kidney failure 95.7%.