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Investigating Diabetic Subjects on Their Correlation With TTH and CAD: A Statistical Approach on Experimental Results
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Author(s): Rohit Rastogi (Dayalbagh Educational Institute, Agra, India & ABES Engineering College, Ghaziabad, India), Devendra K. Chaturvedi (Dayalbagh Educational Institute, Agra, India), Parul Singhal (ABES Engineering College, Ghaziabad, India)and Mayank Gupta (Tata Consultancy Services, Noida, India)
Copyright: 2020
Pages: 24
Source title:
Opportunities and Challenges in Digital Healthcare Innovation
Source Author(s)/Editor(s): Kamaljeet Sandhu (University of New England, Australia)
DOI: 10.4018/978-1-7998-3274-4.ch012
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Abstract
Digital technology is modernizing healthcare. Large volumes of data refer to big data by digitising health information that can quickly be processed by machines. Digital healthcare analysis is the ability to diagnose and suggest ways to reduce costs; provide quality patient care and outcomes, available 24/7; reach to patients located in vast distant geographical areas; and avert preventable diseases. Artificial intelligence (AI) is an autonomous real-time machine system in comparison to natural information analyzed by humans. Diabetes is a serious, under-reported, life-threatening disease affecting millions of people of all ages, and researchers have identified it to be a major public health problem that is approaching epidemic proportions globally. The purpose of this study is to investigate diabetes analysis from CAD and other diseases using the latest advanced digital technologies to analyze information extracted from IoT and big data and stress correlation (TTH) on human health.
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