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Presently, Internet of Things (IoT) and cloud computing (CC) technologies offers a variety of applications and services in the medical field. In a distributed healthcare management, several IoT devices are utilized for monitoring the health condition of the people and forward the data to the cloud for examination. This study introduces an effective IoT and cloud based intelligent distributed disease diagnosis model using deep belief network (DBN). The presented DBN model primarily acquires the medical data from distinct resources. Next, the gathered data is sent to the cloud for further computation. The DBN model is implemented on the cloud to categorize the patient data into the presence of diseases. The DBN model helps to achieve proficient classifier results on the applied data. The results of the DBN model are examined under two medical dataset namely diabetes and heart disease. The experimental results demonstrated that the DBN model is found to be superior to existing methods by offering a maximum of 97.49% and 95.89% on the test diabetes and heart disease correspondingly.
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