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      Integration of 5G and Block-Chain Technologies in Smart Telemedicine Using IoT

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          Abstract

          The Internet of Health Thing (IoHT) has various applications in healthcare. Modern IoHTintegrates health-related things like sensors and remotely observed medical devices for the assessment and managment of a patient's record to provide smarter and efficient health diagnostics to the patient. In this paper, we proposed an IoT with a cloud-based clinical decision support system for prediction and observation of disease with its severity level with the integration of 5G services and block-chain technologies. A block-chain is a system for storing and sharing information that is secure because of its transparency. Block-chain has many applications in healthcare and can improve mobile health applications, monitoring devices, sharing and storing of the electronic media records, clinical trial data, and insurance information storage. The proposed framework will collect the data of patients through medical devices that will be attached to the patient, and these data will be stored in a cloud server with relevant medical records. Deployment of Block-chain and 5G technology allows for sending patient data securely at a fast transmission rate with efficient response time. Furthermore, a Neural Network (NN) classifier is used for the prediction of diseases and their severity level. The proposed model is validated by employing different classifiers. The performance of different classifiers is measured by comparing the values to select the classifier that is the best for the dataset. The NN classifier attains an accuracy of 98.98. Furthermore, the NN is trained for the dataset so that it can predict the result of the dataset class that is not labeled. The trained Neural Network predicts and intelligently shows the results with more accuracy than other classifiers.

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          The Internet of Things: A survey

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            Blockchain in healthcare applications: Research challenges and opportunities

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              Blockchain for 5G-enabled IoT for industrial automation: A systematic review, solutions, and challenges

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                Author and article information

                Contributors
                Journal
                J Healthc Eng
                J Healthc Eng
                JHE
                Journal of Healthcare Engineering
                Hindawi
                2040-2295
                2040-2309
                2021
                22 March 2021
                : 2021
                : 8814364
                Affiliations
                1Department of Computer Science, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan
                2Department of Computer Science, Bahria University, Lahore, Pakistan
                Author notes

                Academic Editor: B. B. Gupta

                Author information
                https://orcid.org/0000-0002-9578-9651
                https://orcid.org/0000-0002-5161-6441
                https://orcid.org/0000-0001-8681-6382
                https://orcid.org/0000-0002-2374-6951
                https://orcid.org/0000-0002-3754-3450
                https://orcid.org/0000-0002-1275-0138
                Article
                10.1155/2021/8814364
                8007349
                a834f7a4-f470-4a2d-944e-bad0c061ed07
                Copyright © 2021 Kashif Hameed et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 6 August 2020
                : 17 December 2020
                : 3 March 2021
                Categories
                Research Article

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