Implementation of Health Monitoring System for Patients using Machine Learning Algorithms
To enhance monitoring and forecasting skills, we investigate in this research study the inclusion of cutting-edge technology in the industrial and healthcare domains. We created a machinelearning- based solution for the wellness program industry that uses Internet Of Medical Things (IoMT) devices...
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2024
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my-inti-eprints.20892024-12-12T09:15:04Z http://eprints.intimal.edu.my/2089/ Implementation of Health Monitoring System for Patients using Machine Learning Algorithms Hariprasad, U.S. UshaSree, R. QA75 Electronic computers. Computer science RA Public aspects of medicine T Technology (General) To enhance monitoring and forecasting skills, we investigate in this research study the inclusion of cutting-edge technology in the industrial and healthcare domains. We created a machinelearning- based solution for the wellness program industry that uses Internet Of Medical Things (IoMT) devices to forecast cardiovascular risk. Our model outperformed previous approaches in diagnosing cardiovascular disease (CVD) with higher accuracy, recall, and F1-score. It did this by using a fuzzy logic classifier for illness prediction and a random forest for feature selection. Additionally, to enhance overall equipment effectiveness (OEE), lower electricity costs, and decrease unplanned downtime in manufacturing settings, we created a real-time system leveraging smart systems and machine learning. During testing on a manufacturing blender, this device tracked operational phases and load-balancing conditions well. We employed the Decision Tree Algorithm to train and assess a model that produced a perfection of 66.66%. INTI International University 2024-12 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2089/1/joit2024_39.pdf text en cc_by_4 http://eprints.intimal.edu.my/2089/2/628 Hariprasad, U.S. and UshaSree, R. (2024) Implementation of Health Monitoring System for Patients using Machine Learning Algorithms. Journal of Innovation and Technology, 2024 (39). pp. 1-7. ISSN 2805-5179 http://ipublishing.intimal.edu.my/joint.html |
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QA75 Electronic computers. Computer science RA Public aspects of medicine T Technology (General) Hariprasad, U.S. UshaSree, R. Implementation of Health Monitoring System for Patients using Machine Learning Algorithms |
| description |
To enhance monitoring and forecasting skills, we investigate in this research study the inclusion
of cutting-edge technology in the industrial and healthcare domains. We created a machinelearning-
based solution for the wellness program industry that uses Internet Of Medical Things
(IoMT) devices to forecast cardiovascular risk. Our model outperformed previous approaches
in diagnosing cardiovascular disease (CVD) with higher accuracy, recall, and F1-score. It did
this by using a fuzzy logic classifier for illness prediction and a random forest for feature
selection. Additionally, to enhance overall equipment effectiveness (OEE), lower electricity
costs, and decrease unplanned downtime in manufacturing settings, we created a real-time
system leveraging smart systems and machine learning. During testing on a manufacturing
blender, this device tracked operational phases and load-balancing conditions well. We
employed the Decision Tree Algorithm to train and assess a model that produced a perfection
of 66.66%. |
| format |
Article |
| author |
Hariprasad, U.S. UshaSree, R. |
| author_facet |
Hariprasad, U.S. UshaSree, R. |
| author_sort |
Hariprasad, U.S. |
| title |
Implementation of Health Monitoring System for Patients using Machine Learning Algorithms |
| title_short |
Implementation of Health Monitoring System for Patients using Machine Learning Algorithms |
| title_full |
Implementation of Health Monitoring System for Patients using Machine Learning Algorithms |
| title_fullStr |
Implementation of Health Monitoring System for Patients using Machine Learning Algorithms |
| title_full_unstemmed |
Implementation of Health Monitoring System for Patients using Machine Learning Algorithms |
| title_sort |
implementation of health monitoring system for patients using machine learning algorithms |
| publisher |
INTI International University |
| publishDate |
2024 |
| url |
http://eprints.intimal.edu.my/2089/1/joit2024_39.pdf http://eprints.intimal.edu.my/2089/2/628 http://eprints.intimal.edu.my/2089/ http://ipublishing.intimal.edu.my/joint.html |
| _version_ |
1818840134790938624 |
| score |
13.222552 |