IOT based wearable sensor for diseases prediction and symptom analysis in healthcare sector
Abstract
Humans with good health condition is some more difficult in today’s life, because of changing food habit and environment. So we need awareness about the health condition to the survival. The health-support systems faces significant challenges like lack of adequate medical information, preventable errors, data threat, misdiagnosis, and delayed transmission. To overcome this problem, here we proposed wearable sensor which is connected to Internet of things (IoT) based big data ie data mining analysis in healthcare. Moreover, here we design Generalize approximate Reasoning base Intelligence Control (GARIC) with regression rules to gather the information about the patient from the IoT. Finally, Train the data to the Artificial intelligence (AI) with the use of deep learning mechanism Boltzmann belief network. Subsequently Regularization _ Genome wide association study (GWAS) is used to predict the diseases.
Author(s)
seifedine kadry
Journal/Conference Information
Peer-to-peer networking and applications
,DOI: https://doi.org/10.1007/s12083-019-00823-2, ISSN: 19366450, Volume: 60, Issue: 5, Pages Range: 1-12,