Systematic review of smart health monitoring using deep learning and Artificial intelligence
In the rapidly growing world of technology and evolution, the outbreak and emergences diseases have become a critical issue. Precaution, prevention and controlling the diseases by technology has become the major challenge for healthcare professionals and health care industries. Maintaining a healthy...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-09-01
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| Series: | Neuroscience Informatics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772528621000285 |
| _version_ | 1798035962379370496 |
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| author | A.V.L.N. Sujith Guna Sekhar Sajja V. Mahalakshmi Shibili Nuhmani B. Prasanalakshmi |
| author_facet | A.V.L.N. Sujith Guna Sekhar Sajja V. Mahalakshmi Shibili Nuhmani B. Prasanalakshmi |
| author_sort | A.V.L.N. Sujith |
| collection | DOAJ |
| description | In the rapidly growing world of technology and evolution, the outbreak and emergences diseases have become a critical issue. Precaution, prevention and controlling the diseases by technology has become the major challenge for healthcare professionals and health care industries. Maintaining a healthy lifestyle has become impossible in the busy work schedules. Smart health monitoring system is the solution to the above poses challenges. The recent revolution of industry 5.0 and 5G has led to development of smart cum cost effective sensors which help in real time health monitoring or individuals. The SHM has led to fast, cost effective, and reliable health monitoring services from remote locations which was not possible with traditional health care systems. The integration of blockchain framework improved data security and data privacy of confidential data of patient to prevent the data misuse against patients. Involvement of Deep Learning and Machine learning to analyze health data to achieve multiple targets has helped attain preventive healthcare and fatality management in patients. This has helped in the early detection of chronic diseases which was not possible recently. To make the services more cost effective and real time, the integration of cloud computing and cloud storage has been implemented. The work presents the systematic review of SHM along with recent advancements in SHM with existing challenges. |
| first_indexed | 2024-04-11T21:05:52Z |
| format | Article |
| id | doaj.art-6b2146f52b884242bc73add756dbc5de |
| institution | Directory Open Access Journal |
| issn | 2772-5286 |
| language | English |
| last_indexed | 2024-04-11T21:05:52Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Neuroscience Informatics |
| spelling | doaj.art-6b2146f52b884242bc73add756dbc5de2022-12-22T04:03:16ZengElsevierNeuroscience Informatics2772-52862022-09-0123100028Systematic review of smart health monitoring using deep learning and Artificial intelligenceA.V.L.N. Sujith0Guna Sekhar Sajja1V. Mahalakshmi2Shibili Nuhmani3B. Prasanalakshmi4Department of Computer Science and Engineering, Anantha Lakshmi Institute of Technology and Sciences, Ananthapuramu, AP, IndiaInformation Technology Department, University of the Cumberlands, Williamsburg, KY 40769, United States of America; Corresponding author.Department of Computer Science, College of Computer Science & Information Technology, Jazan University, Saudi ArabiaDepartment of Physical Therapy, Imam Abdulrahman Bin Faisal University, Dammam, Saudi ArabiaCenter for Artificial Intelligence, King Khalid University, Saudi ArabiaIn the rapidly growing world of technology and evolution, the outbreak and emergences diseases have become a critical issue. Precaution, prevention and controlling the diseases by technology has become the major challenge for healthcare professionals and health care industries. Maintaining a healthy lifestyle has become impossible in the busy work schedules. Smart health monitoring system is the solution to the above poses challenges. The recent revolution of industry 5.0 and 5G has led to development of smart cum cost effective sensors which help in real time health monitoring or individuals. The SHM has led to fast, cost effective, and reliable health monitoring services from remote locations which was not possible with traditional health care systems. The integration of blockchain framework improved data security and data privacy of confidential data of patient to prevent the data misuse against patients. Involvement of Deep Learning and Machine learning to analyze health data to achieve multiple targets has helped attain preventive healthcare and fatality management in patients. This has helped in the early detection of chronic diseases which was not possible recently. To make the services more cost effective and real time, the integration of cloud computing and cloud storage has been implemented. The work presents the systematic review of SHM along with recent advancements in SHM with existing challenges.http://www.sciencedirect.com/science/article/pii/S2772528621000285Smart health monitoringBlockchainDeep learningRemote health monitoring |
| spellingShingle | A.V.L.N. Sujith Guna Sekhar Sajja V. Mahalakshmi Shibili Nuhmani B. Prasanalakshmi Systematic review of smart health monitoring using deep learning and Artificial intelligence Neuroscience Informatics Smart health monitoring Blockchain Deep learning Remote health monitoring |
| title | Systematic review of smart health monitoring using deep learning and Artificial intelligence |
| title_full | Systematic review of smart health monitoring using deep learning and Artificial intelligence |
| title_fullStr | Systematic review of smart health monitoring using deep learning and Artificial intelligence |
| title_full_unstemmed | Systematic review of smart health monitoring using deep learning and Artificial intelligence |
| title_short | Systematic review of smart health monitoring using deep learning and Artificial intelligence |
| title_sort | systematic review of smart health monitoring using deep learning and artificial intelligence |
| topic | Smart health monitoring Blockchain Deep learning Remote health monitoring |
| url | http://www.sciencedirect.com/science/article/pii/S2772528621000285 |
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