M. Afshar Alam

Sherin Zafar

S. N. Kumar

Eduard Babulak

Farheen Siddiqui

This book explores the role of artificial Intelligence in Telemedicine. It explains the concepts through the detailed study and processing of biosignals, physiological parameters, and medical images. The book focuses on computational algorithms in telemedicine for the processing of biosignals, physiological parameters, and medical Images. The book is presented in two section. The first section presents the role of computational algorithms in the processing of biosignal and medical images for disease diagnosis and treatment planning. Noise removal in ECG signal using an improved adaptive learning approach, classification of ECG signals using CNN for cardiac arrhythmia detection, EEG signal analysis for stroke detection, and EMG signal analysis for gesture classification were discussed in this section. Application of CNN in pertussis Diagnosis by temperature monitoring, physician handwriting recognition using deep learning model, melanoma detection using ABCD parameters, and transfer learning enabled heuristic approach for pneumonia detection was also discussed in this section The second section focus on the role of IoT and artificial intelligence in the healthcare sector. IoT in smart health care and applications of artificial intelligence in disease diagnosis and prediction was discussed in this section. The importance of 5G/6G in the pandemic scenario for telemedicine applications, wireless capsule endoscopy image compression, leukemia detection from the microscopic cell images, and genomic signal processing using numerical mapping techniques was also discussed in this section. This book can be used by a wide range of users including students, research scholars, faculty, and practitioners in the field of engineering for applications in biomedical signal, image analysis, and diagnosis.

Processing of Biosignals and Medical images

Artificial Intelligence in Telemedicine

Deepa Mehta

Mohd Abdul Ahad

Syed Imran Ali

SMART AND SUSTAINABLE APPROACHES FOR OPTIMIZING PERFORMANCE OF WIRELESS NETWORK Explores the intersection of sustainable growth, green computing and automation, and performance optimization of 5G wireless networks Smart and Sustainable Approaches for Optimizing Performance of Wireless Networks explores how wireless sensing applications, green computing, and Big Data analytics can increase the energy efficiency and environmental sustainability of real-time applications across areas such as healthcare, agriculture, construction, and manufacturing. Bringing together an international team of expert contributors, this authoritative volume highlights the limitations of conventional technologies and provides methodologies and approaches for addressing Quality of Service (QOS) issues and optimizing network performance. In-depth chapters cover topics including blockchain-assisted secure data sharing, smart 5G Internet of Things (IoT) scenarios, intelligent management of ad hoc networks, and the use of Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) techniques in smart healthcare, smart manufacturing, and smart agriculture. Covers design, implementation, optimization, and sustainability of wireless and sensor-based networks Discusses concepts of sustainability and green computing as well as their relevance to society and the environment Addresses green automation applications in various disciplines such as computer science, nanoscience, information technology (IT), and biochemistry Explores various smart and sustainable approaches for current wireless and sensor-based networks Includes detailed case studies of current methodologies, applications, and implementations Smart and Sustainable Approaches for Optimizing Performance of Wireless Networks: Real-time Applications is an essential resource for academic researchers and industry professionals working to integrate sustainable development and Information and Communications Technology (ICT).

Real-time Applications

Smart and Sustainable Approaches for Optimizing Performance of Wireless Networks

Sheikh Mohammad Idrees

Parul Agarwal

Blockchain for Healthcare Systems: Challenges, Privacy, and Securing of Data provides a detailed insight on how to reap the benefits of blockchain technology in healthcare, as the healthcare sector faces several challenges associated with privacy and security issues. It also provides in-depth knowledge regarding blockchain in healthcare and the underlying components. This book explores securing healthcare data using blockchain technology. It discusses challenges and solutions for blockchain technology in the healthcare sector and presents the digital transformation of the healthcare sector using different technologies. It covers the handling of healthcare data/medical records and managing the medical supply chain all using blockchain technology. The contents of this book are highly beneficial to educators, researchers, and others working in a similar domain.

Challenges, Privacy, and Securing of Data

Blockchain for Healthcare Systems

M. Afshar Alam

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