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  2. Volume 7, Issue 6
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Online ISSN: 2515-8260

Volume7, Issue6

Leveraging Digital Twin Technology in the Healthcare Industry – A Machine Learning Based Approach

    Aashish Bende , Dr. Saikat Gochhait

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 6, Pages 2547-2557

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Abstract

This paper deals with the concept of digital twin technology and leveraging the same in the healthcare domain. Digital twin technology is adding value to the healthcare industry by personalizing the diagnosis and therapy selection procedure. Finite Element Analysis (Finite Element Analysis, 2001) is a simulation method used to create a digital replica or a digital instance of the human organs such as heart, kidney, or brain. IoT devices or sensors such as implantable cardioverter defibrillatoror heart pacemakers collect the medical data of patients, which is analyzed to create a virtual instance using simulation software. The virtual instance is continuously updated and is used in generating reports for further diagnosis.
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(2020). Leveraging Digital Twin Technology in the Healthcare Industry – A Machine Learning Based Approach. European Journal of Molecular & Clinical Medicine, 7(6), 2547-2557.
Aashish Bende , Dr. Saikat Gochhait. "Leveraging Digital Twin Technology in the Healthcare Industry – A Machine Learning Based Approach". European Journal of Molecular & Clinical Medicine, 7, 6, 2020, 2547-2557.
(2020). 'Leveraging Digital Twin Technology in the Healthcare Industry – A Machine Learning Based Approach', European Journal of Molecular & Clinical Medicine, 7(6), pp. 2547-2557.
Leveraging Digital Twin Technology in the Healthcare Industry – A Machine Learning Based Approach. European Journal of Molecular & Clinical Medicine, 2020; 7(6): 2547-2557.
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