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Disease Analysis and Prediction Using Digital Twins and Big Data Analytics
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Author(s): Rajagopal R. (Narsimha Reddy Engineering College, India), Karthikeyan P. (National Chung Cheng University, Taiwan), Menaka E. (Vivekanandha College of Engineering and Technology for Women, India), Karunakaran V. (Jain University (Deemed), India)and Harshavaradhanan Pon (Vellore Institute of Technology, Bhopal, India)
Copyright: 2023
Pages: 17
Source title:
New Approaches to Data Analytics and Internet of Things Through Digital Twin
Source Author(s)/Editor(s): P. Karthikeyan (National Chung Cheng University, Chiayi, Taiwan), Polinpapilinho F. Katina (University of South Carolina Upstate, USA)and S.P. Anandaraj (Presidency University, India)
DOI: 10.4018/978-1-6684-5722-1.ch005
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Abstract
The data generated by the big data-based clinical need analysis plays a key role in improving the consideration feature, decreasing waste and blunder, and reducing treatment expenses. The use of big data analytics (BDA) techniques for analyzing disease and predictions is discussed in this investigation. This precise survey of writing means to decide the extent of BDA in disease analysis and difficulties in treatment in the medical filed. Further, this study has discussed the comparative analysis of heart diseases, predictions using BDA techniques, predicting of breast cancer, lung cancer, and brain diseases. Digital twins will be key to delivering highly personalized treatments and interventions. Intelligent digital twins, combining data, knowledge, and algorithms (AI), are set to revolutionise medicine and public health.
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