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An adaptive medical cyber-physical system for post diagnosis patient care using cloud computing and machine learning approach

Medical care is one of the most basic human needs. Due to the global shortage of doctors, nurses, and other healthcare personnel, medical cyber-physical systems are quickly becoming a viable option. Post-diagnosis surveillance is an essential application of these systems, which can be performed more...

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Main Authors: Miah, Md Saef Ullah, Sarwar, Talha, Islam, Saima Sharleen, Haque, Md Samiul, Masuduzzaman, Md, Bhowmik, Abhijit
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://umpir.ump.edu.my/id/eprint/39429/1/An%20adaptive%20Medical%20Cyber-Physical%20System%20for%20post%20diagnosis.pdf
http://umpir.ump.edu.my/id/eprint/39429/2/An%20adaptive%20medical%20cyber-physical%20system%20for%20post%20diagnosis%20patient%20care%20using%20cloud%20computing%20and%20machine%20learning%20approach_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39429/
https://doi.org/10.1109/INCET54531.2022.9824032
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spelling my.ump.umpir.394292023-11-29T04:25:14Z http://umpir.ump.edu.my/id/eprint/39429/ An adaptive medical cyber-physical system for post diagnosis patient care using cloud computing and machine learning approach Miah, Md Saef Ullah Sarwar, Talha Islam, Saima Sharleen Haque, Md Samiul Masuduzzaman, Md Bhowmik, Abhijit QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) Medical care is one of the most basic human needs. Due to the global shortage of doctors, nurses, and other healthcare personnel, medical cyber-physical systems are quickly becoming a viable option. Post-diagnosis surveillance is an essential application of these systems, which can be performed more successfully using various monitoring devices rather than active observation by nurses in their physical presence. However, most existing solutions for this application are rigid and do not consider current difficulties. Intelligent and adaptive systems can overcome the challenges because of the advances in relevant technology, especially healthcare 4.0. Therefore, this work presents an adaptive system based on cloud and edge computing architecture and machine learning approaches to perform post-diagnosis medical tasks on patients, thus reducing the need for nurses, especially in the post-diagnosis phase. Institute of Electrical and Electronics Engineers Inc. 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39429/1/An%20adaptive%20Medical%20Cyber-Physical%20System%20for%20post%20diagnosis.pdf pdf en http://umpir.ump.edu.my/id/eprint/39429/2/An%20adaptive%20medical%20cyber-physical%20system%20for%20post%20diagnosis%20patient%20care%20using%20cloud%20computing%20and%20machine%20learning%20approach_ABS.pdf Miah, Md Saef Ullah and Sarwar, Talha and Islam, Saima Sharleen and Haque, Md Samiul and Masuduzzaman, Md and Bhowmik, Abhijit (2022) An adaptive medical cyber-physical system for post diagnosis patient care using cloud computing and machine learning approach. In: 2022 3rd International Conference for Emerging Technology, INCET 2022, 27-29 May 2022 , Belgaum. pp. 1-6. (180997). ISBN 978-166549499-1 https://doi.org/10.1109/INCET54531.2022.9824032
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Miah, Md Saef Ullah
Sarwar, Talha
Islam, Saima Sharleen
Haque, Md Samiul
Masuduzzaman, Md
Bhowmik, Abhijit
An adaptive medical cyber-physical system for post diagnosis patient care using cloud computing and machine learning approach
description Medical care is one of the most basic human needs. Due to the global shortage of doctors, nurses, and other healthcare personnel, medical cyber-physical systems are quickly becoming a viable option. Post-diagnosis surveillance is an essential application of these systems, which can be performed more successfully using various monitoring devices rather than active observation by nurses in their physical presence. However, most existing solutions for this application are rigid and do not consider current difficulties. Intelligent and adaptive systems can overcome the challenges because of the advances in relevant technology, especially healthcare 4.0. Therefore, this work presents an adaptive system based on cloud and edge computing architecture and machine learning approaches to perform post-diagnosis medical tasks on patients, thus reducing the need for nurses, especially in the post-diagnosis phase.
format Conference or Workshop Item
author Miah, Md Saef Ullah
Sarwar, Talha
Islam, Saima Sharleen
Haque, Md Samiul
Masuduzzaman, Md
Bhowmik, Abhijit
author_facet Miah, Md Saef Ullah
Sarwar, Talha
Islam, Saima Sharleen
Haque, Md Samiul
Masuduzzaman, Md
Bhowmik, Abhijit
author_sort Miah, Md Saef Ullah
title An adaptive medical cyber-physical system for post diagnosis patient care using cloud computing and machine learning approach
title_short An adaptive medical cyber-physical system for post diagnosis patient care using cloud computing and machine learning approach
title_full An adaptive medical cyber-physical system for post diagnosis patient care using cloud computing and machine learning approach
title_fullStr An adaptive medical cyber-physical system for post diagnosis patient care using cloud computing and machine learning approach
title_full_unstemmed An adaptive medical cyber-physical system for post diagnosis patient care using cloud computing and machine learning approach
title_sort adaptive medical cyber-physical system for post diagnosis patient care using cloud computing and machine learning approach
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/39429/1/An%20adaptive%20Medical%20Cyber-Physical%20System%20for%20post%20diagnosis.pdf
http://umpir.ump.edu.my/id/eprint/39429/2/An%20adaptive%20medical%20cyber-physical%20system%20for%20post%20diagnosis%20patient%20care%20using%20cloud%20computing%20and%20machine%20learning%20approach_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39429/
https://doi.org/10.1109/INCET54531.2022.9824032
_version_ 1822923875231465472
score 13.23243

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