Cloud Based Healthcare Framework for Criticality Level Analysis
Sindhushree B1, Manishankar S2, Dhanushya B P3
1Sindhushree B, pursuing her Master of Computer Applications (MCA) Amrita School of Arts & Sciences, Mysuru (Karnataka), India.
2Manishankar S, Assistant Professor, Department of Computer Sciences, Amrita Vishwa Vidyapeetham, Mysuru (Karnataka), India.
3Dhanushya B P, student of Amrita School of Arts and Sciences, Mysuru, Amrita Vishwa Vidyapeetham (Tamil Nadu), India.
Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 1819-1823 | Volume-8 Issue-5, June 2019 | Retrieval Number: E7614068519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In a Cloud based development Amazon Web Service(AWS) is a platform which secures the cloud services, offers database storage, content delivery, computer power and also provides other functionality to help business scale and grow. This proposed work aims that medical healthcare inputs from various sensors have been automatically retrieved and directly loaded into the cloud. Once the data has been loaded creating the inference engine, setting up a big data cloud environment and store the data into a cloud based dataset. Medical data is calculated using machine learning algorithms such as K-Nearest Neighbor (KNN), Naïve Bayes and Support Vector Machine (SVM) through R shiny web application. The cloud system stores the health care data and transmitted to practitioners through the web service network. Based on these medical data the score value of a patient is calculated and displays criticality of patient.
Keywords: Amazon Web Service (AWS), K-Nearest Neighbor(KNN), Naïve Bayes(NB), Support Vector Machine(SVM).
Scope of the Article: Web Technologies