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Applications of Artificial Intelligence in E-Healthcare Systems

Applications of Artificial Intelligence in E-Healthcare Systems

Edited by Munish Sabharwal, B. Balamurugan Balusamy, S. Rakesh Kumar, N. Gayathri, Shakhzod Suvanov

Increased use of artificial intelligence (AI) is being deployed in many hospitals and healthcare settings to help improve health care service delivery. Machine learning (ML) and deep learning (DL) tools can help guide physicians with tasks such as diagnosis and detection of diseases and assisting with medical decision making.

This edited book outlines novel applications of AI in e-healthcare. It includes various real-time/offline applications and case studies in the field of e-Healthcare, such as image recognition tools for assisting with tuberculosis diagnosis from x-ray data, ML tools for cancer disease prediction, and visualisation techniques for predicting the outbreak and spread of Covid-19.

Heterogenous recurrent convolution neural networks for risk prediction in electronic healthcare record datasets are also reviewed.

Suitable for an audience of computer scientists and healthcare engineers, the main objective of this book is to demonstrate effective use of AI in healthcare by describing and promoting innovative case studies and finding the scope for improvement across healthcare services.

About the Editors

Munish Sabharwal is a professor and the dean of the School of Computing Science and Engineering at Galgotias University, India. He is a member of numerous engineering societies spanning USA, Singapore, India, and China and a fellow of the Centre for Education Growth and Research (India) and of the Institute of Electronics and Telecommunication Engineers (India). His research interests include Artificial Intelligence, Machine Learning, Biometrics, and E-Banking.

B. Balamurugan Balusamy is an associate Dean-Student Engagement at Shiv Nadar University, Delhi-National Capital Region (NCR), India. He is a previous recipient of the IBM Developer Superstar Award and the CSC-VIT Best Faculty Coordinator Award. His current research interests include Internet of Things technologies and blockchain applications for healthcare. He is a member of Association for Computing Machinery, the Computer Society of India, and the International Association of Engineers.

S. Rakesh Kumar is an assistant professor of Computer Science at Galgotias University, India. His research interests include big data analytics, Internet of Things technologies, artificial intelligence and machine learning. He is a member of Association for Computing Machinery, the Computer Society of India, and the International Association of Engineers.

N. Gayathri is an associate professor of Computer Science and Engineering at Galgotias University, India. She is a member of Association for Computing Machinery, the Computer Society of India, and the International Association of Engineers.

Shakhzod Suvanov is a lecturer and research scholar in the Faculty of Digital Technologies at Samarkand State University, Uzbekistan. His research interests include machine learning, artificial neural network, mathematical modeling, and dynamical systems.



Item Subjects:
Healthcare Technologies

Publication Year: 2022

Pages: 306

ISBN-13: 978-1-83953-449-2

Format: HBK

Editors: Munish Sabharwal, B. Balamurugan Balusamy, S. Rakesh Kumar, N. Gayathri, Shakhzod Suvanov

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