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Tele-Healthcare : Applications of Artificial Intelligence and Soft Computing Techniques

By: (Edited by) Manish Kumar , (Edited by) R. Nidhya , (Edited by) India) Balamurugan S.

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Ksh 30,600.00

Format: Hardback or Cased Book

ISBN-10: 1119841763

ISBN-13: 9781119841760

Publisher: John Wiley & Sons Inc

Imprint: Wiley-Scrivener

Country of Manufacture: US

Country of Publication: GB

Publication Date: Jul 13th, 2022

Print length: 416 Pages

Weight: 454 grams

Dimensions (height x width x thickness): 1.00 x 1.00 x 1.00 cms

Product Classification: Biotechnology
Artificial intelligence

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TELE-HEALTHCARE This book elucidates all aspects of tele-healthcare which is the application of AI, soft computing, digital information, and communication technologies, to provide services remotely and manage one’s healthcare. Throughout the world, there are huge developing crises with respect to healthcare workforce shortages, as well as a growing burden of chronic diseases. As a result, e-health has become one of the fastest-growing service areas in the medical sector. E-health supports and ensures the availability of proper healthcare, public health, and health education services at a distance and in remote places. For the sector to grow and meet the need of the marketplace, e-health applications have become one of the fastest growing areas of research. However, to grow at a larger scale requires the following: The availability of user cases for the exact identification of problems that need to be visualized. A well-supported market that can promote and adopt the e-health care concept. Development of cost-effectiveness applications and technologies for successful implementation of e-health at a larger scale. This book mainly focuses on these three points for the development and implementation of e-health services globally. In this book the reader will find: Details of the challenges in promoting and implementing the telehealth industry. How to expand a globalized agenda of personalized telehealth in integrative medical treatment for disease diagnosis and its industrial transformation. How to design machine learning techniques for improving the tele-healthcare system. Audience Researchers and post-graduate students in biomedical engineering, artificial intelligence, and information technology; medical doctors and practitioners and industry experts in the healthcare sector; healthcare sector network administrators.

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