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Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System
Blockchain is a recent revolutionary technology primarily associated with cryptocurrencies. It has many unique features including its acting as a decentralized, immutable, shared, and distributed ledger. Blockchain can store all types of data with better security. It avoids third-party intervention...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122032/ https://www.ncbi.nlm.nih.gov/pubmed/35602165 http://dx.doi.org/10.3389/fpubh.2022.905265 |
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author | Mantey, Eric Appiah Zhou, Conghua Srividhya, S. R. Jain, Sanjiv Kumar Sundaravadivazhagan, B. |
author_facet | Mantey, Eric Appiah Zhou, Conghua Srividhya, S. R. Jain, Sanjiv Kumar Sundaravadivazhagan, B. |
author_sort | Mantey, Eric Appiah |
collection | PubMed |
description | Blockchain is a recent revolutionary technology primarily associated with cryptocurrencies. It has many unique features including its acting as a decentralized, immutable, shared, and distributed ledger. Blockchain can store all types of data with better security. It avoids third-party intervention to ensure better security of the data. Deep learning is another booming field that is mostly used in computer applications. This work proposes an integrated environment of a blockchain-deep learning environment for analyzing the Electronic Health Records (EHR). The EHR is the medical documentation of a patient which can be shared among hospitals and other public health organizations. The proposed work enables a deep learning algorithm act as an agent to analyze the EHR data which is stored in the blockchain. This proposed integrated environment can alert the patients by means of a reminder for consultation, diet chart, etc. This work utilizes the deep learning approach to analyze the EHR, after which an alert will be sent to the patient's registered mobile number. |
format | Online Article Text |
id | pubmed-9122032 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91220322022-05-21 Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System Mantey, Eric Appiah Zhou, Conghua Srividhya, S. R. Jain, Sanjiv Kumar Sundaravadivazhagan, B. Front Public Health Public Health Blockchain is a recent revolutionary technology primarily associated with cryptocurrencies. It has many unique features including its acting as a decentralized, immutable, shared, and distributed ledger. Blockchain can store all types of data with better security. It avoids third-party intervention to ensure better security of the data. Deep learning is another booming field that is mostly used in computer applications. This work proposes an integrated environment of a blockchain-deep learning environment for analyzing the Electronic Health Records (EHR). The EHR is the medical documentation of a patient which can be shared among hospitals and other public health organizations. The proposed work enables a deep learning algorithm act as an agent to analyze the EHR data which is stored in the blockchain. This proposed integrated environment can alert the patients by means of a reminder for consultation, diet chart, etc. This work utilizes the deep learning approach to analyze the EHR, after which an alert will be sent to the patient's registered mobile number. Frontiers Media S.A. 2022-05-06 /pmc/articles/PMC9122032/ /pubmed/35602165 http://dx.doi.org/10.3389/fpubh.2022.905265 Text en Copyright © 2022 Mantey, Zhou, Srividhya, Jain and Sundaravadivazhagan. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Mantey, Eric Appiah Zhou, Conghua Srividhya, S. R. Jain, Sanjiv Kumar Sundaravadivazhagan, B. Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System |
title | Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System |
title_full | Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System |
title_fullStr | Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System |
title_full_unstemmed | Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System |
title_short | Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System |
title_sort | integrated blockchain-deep learning approach for analyzing the electronic health records recommender system |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122032/ https://www.ncbi.nlm.nih.gov/pubmed/35602165 http://dx.doi.org/10.3389/fpubh.2022.905265 |
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