ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774


EFFICIENT REMOTE CLINICAL DECISION SERVICES USING MACHINE LEARNING IN CLOUD COMPUTING: A REVIEW

Abstract

Abstract: - Earlier as well as nowadays also, the doctors are using trial and error approach for predicting the diseases based on clinical investigations available. Remote clinical decision services is one of the major challenges in past years and today also. There is great need of some system that predicts the diseases,hospitals early on the basis of available symptoms and patients health. Because of this it will become possible to cure the people from diseases which may lead the humans to death. We are a proposing system which is based on combination of different locations, doctor’s details, disease symptoms and disease treatment that are useful to predict the patient’s disease. The patient's disease states can be finding out by formalizing the disease based on symptoms of the patient before recommending treatments for the prevailing diseases by using machine learning Classification techniques respectively. The basic aim of our system is to assist doctors in diagnosingthe patient by analyzing disease symptoms and relevant information. As our project's main focus is providing remote clinical decision services to people living in rural areas to provide them with free treatment for general diseases which they tend to neglect. Keywords— Cloud computing, data privacy, medical services, Machine Learning, encryption.

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Paper Submission Open For October 2024
UGC indexed in (Old UGC) 2017
Last date for paper submission 30th October, 2024
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Publication of Paper Within 15-30 Days after completing all the formalities
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Publication Fees  Rs.8000 (PG student)