This book focusses on the Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Health-Care.

The Reader will be able to know the recent advancements in Microwave Engineering including novel techniques in Microwave Antenna Design and various aspects of Microwave Propagation. This book aims to showcase, the various aspects of Communication, Networking, Data Mining, Computational Biology, Bioinformatics, Bio-Statistics and Machine Learning.

In this book, recent trends in Solid State Technologies, VLSI and applicability of modern Electronic Devices in Bio-informatics and Health-Care is focused. Furthermore, this book showcases the modern optimization techniques in Power System Engineering, Machine Design and Power Systems.

This Book highlights the Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Health-Care for day-to-day applications.

Societal benefits of Microwave Technologies for smooth and hustle-free life are also areas of major focus. Microwave Engineering includes recent advancements and novel techniques in Microwave Antenna Design and various aspects of Microwave Propagation.

Day-to-Day applicability of modern communication and networking technologies are a matter of prime concern. This book aims to showcase, the various aspects of Communication, Networking, Data Mining, Computational Biology, Bioinformatics, Bio-Statistics and Machine Learning.

Role of Solid Sate Engineering in development of modern electronic gadgets are discussed. In this book, recent trends in Solid State Technologies, VLSI and applicability of modern Electronic Devices in Bio-informatics and Biosensing Devices for Smart Health care are also discussed.

Features:

This book focusses on the Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Health-Care.

The Reader will be able to know the recent advancements in Microwave Engineering including novel techniques in Microwave Antenna Design and various aspects of Microwave Propagation. This book aims to showcase, the various aspects of Communication, Networking, Data Mining, Computational Biology, Bioinformatics, Bio-Statistics and Machine Learning.

In this book, recent trends in Solid State Technologies, VLSI and applicability of modern Electronic Devices in Bio-informatics and Health-Care is focused. Furthermore, this book showcases the modern optimization techniques in Power System Engineering, Machine Design and Power Systems.

This Book highlights the Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Health-Care for day-to-day applications.

Societal benefits of Microwave Technologies for smooth and hustle-free life are also areas of major focus. Microwave Engineering includes recent advancements and novel techniques in Microwave Antenna Design and various aspects of Microwave Propagation.

Day-to-Day applicability of modern communication and networking technologies are a matter of prime concern. This book aims to showcase, the various aspects of Communication, Networking, Data Mining, Computational Biology, Bioinformatics, Bio-Statistics and Machine Learning.

Role of Solid Sate Engineering in development of modern electronic gadgets are discussed. In this book, recent trends in Solid State Technologies, VLSI and applicability of modern Electronic Devices in Bio-informatics and Biosensing Devices for Smart Health care are also discussed.

Features:

This book focuses on an eminent technology called next generation sequencing (NGS) which has entirely changed the procedure of examining organisms and will have a great impact on biomedical research and disease diagnosis. Numerous computational challenges have been brought on by the rapid advancement of large-scale next-generation sequencing (NGS) technologies and their application. The term ""biomedical imaging"" refers to the use of a variety of imaging techniques (such as X-rays, CT scans, MRIs, ultrasounds, etc.) to get images of the interior organs of a human being for potential diagnostic, treatment planning, follow-up, and surgical purposes. In these circumstances, deep learning, a new learning method that uses multi-layered artificial neural networks (ANNs) for unsupervised, supervised, and semi-supervised learning, has attracted a lot of interest for applications to NGS and imaging, even when both of these data are used for the same group of patients.

The three main research phenomena in biomedical research are disease classification, feature dimension reduction, and heterogeneity. AI approaches are used by clinical researchers to efficiently analyse extremely complicated biomedical datasets (e.g., multi-omic datasets. With the use of NGS data and biomedical imaging of various human organs, researchers may predict diseases using a variety of deep learning models. Unparalleled prospects to improve the work of radiologists, clinicians, and biomedical researchers, speed up disease detection and diagnosis, reduce treatment costs, and improve public health are presented by using deep learning models in disease prediction using NGS and biomedical imaging. This book influences a variety of critical disease data and medical images.

This book looks at the integration of blockchain technology in healthcare settings, focusing on its potential to address security and privacy concerns of medical applications. From fragmented electronic health records (EHRs) to data breaches and interoperability issues, innovative solutions are necessary to unlock the full potential of health information and prevent the recurrence of such issues.

Blockchain offers a promising framework for addressing these challenges. Its decentralized, tamper-resistant nature holds the key to building trust and transparency in healthcare data management. By leveraging blockchain technology, secure, interoperable systems empower patients to take control of their health information while facilitating a seamless collaboration among healthcare providers. Throughout this book, the authors explore the fundamental principles of blockchain technology and its applications within the healthcare landscape. From EHRs and patient consent management to pharmaceutical supply chains and clinical research, this book examines how blockchain can drive efficiency, enhance security, and ultimately improve patient outcomes.

This book is intended for a broad audience, including healthcare professionals, patients, policymakers, and anyone interested in the intersection of technology and healthcare.

This book looks at the integration of blockchain technology in healthcare settings, focusing on its potential to address security and privacy concerns of medical applications. From fragmented electronic health records (EHRs) to data breaches and interoperability issues, innovative solutions are necessary to unlock the full potential of health information and prevent the recurrence of such issues.

Blockchain offers a promising framework for addressing these challenges. Its decentralized, tamper-resistant nature holds the key to building trust and transparency in healthcare data management. By leveraging blockchain technology, secure, interoperable systems empower patients to take control of their health information while facilitating a seamless collaboration among healthcare providers. Throughout this book, the authors explore the fundamental principles of blockchain technology and its applications within the healthcare landscape. From EHRs and patient consent management to pharmaceutical supply chains and clinical research, this book examines how blockchain can drive efficiency, enhance security, and ultimately improve patient outcomes.

This book is intended for a broad audience, including healthcare professionals, patients, policymakers, and anyone interested in the intersection of technology and healthcare.

Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medical diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep learning (DL) techniques are widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. However, accuracy and reliability in model performance can be a concern in tackling data generated from medical images and signals, making it challenging for researchers and practitioners. Therefore, optimized models can produce quality healthcare services to handle the complexities involved in biomedical research.

Various optimization techniques have been employed to optimize parameters, hyper-parameters, and architectural information of ML/DL models explicitly applied to biological, medical, and signal data. The swarm intelligence approach has the potential to solve complex non-linear optimization problems. It mimics the collective behavior of social swarms such as ant colonies, honey bees, and bird flocks. The cooperative nature of swarms can search global settings of ML/DL models, which efficiently provide the solution to biomedical engineering applications. Finally, the book aims to provide the utility of swarm optimization and similar optimization techniques to design ML/DL models to improve the solutions related to biomedical engineering.

Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medical diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep learning (DL) techniques are widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. However, accuracy and reliability in model performance can be a concern in tackling data generated from medical images and signals, making it challenging for researchers and practitioners. Therefore, optimized models can produce quality healthcare services to handle the complexities involved in biomedical research.

Various optimization techniques have been employed to optimize parameters, hyper-parameters, and architectural information of ML/DL models explicitly applied to biological, medical, and signal data. The swarm intelligence approach has the potential to solve complex non-linear optimization problems. It mimics the collective behavior of social swarms such as ant colonies, honey bees, and bird flocks. The cooperative nature of swarms can search global settings of ML/DL models, which efficiently provide the solution to biomedical engineering applications. Finally, the book aims to provide the utility of swarm optimization and similar optimization techniques to design ML/DL models to improve the solutions related to biomedical engineering.

This book focusses on the Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Health-Care.

The Reader will be able to know the recent advancements in Microwave Engineering including novel techniques in Microwave Antenna Design and various aspects of Microwave Propagation. This book aims to showcase, the various aspects of Communication, Networking, Data Mining, Computational Biology, Bioinformatics, Bio-Statistics and Machine Learning.

In this book, recent trends in Solid State Technologies, VLSI and applicability of modern Electronic Devices in Bio-informatics and Health-Care is focused. Furthermore, this book showcases the modern optimization techniques in Power System Engineering, Machine Design and Power Systems.

This Book highlights the Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Health-Care for day-to-day applications.

Societal benefits of Microwave Technologies for smooth and hustle-free life are also areas of major focus. Microwave Engineering includes recent advancements and novel techniques in Microwave Antenna Design and various aspects of Microwave Propagation.

Day-to-Day applicability of modern communication and networking technologies are a matter of prime concern. This book aims to showcase, the various aspects of Communication, Networking, Data Mining, Computational Biology, Bioinformatics, Bio-Statistics and Machine Learning.

Role of Solid Sate Engineering in development of modern electronic gadgets are discussed. In this book, recent trends in Solid State Technologies, VLSI and applicability of modern Electronic Devices in Bio-informatics and Biosensing Devices for Smart Health care are also discussed.

Features:

This book focusses on the Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Health-Care.

The Reader will be able to know the recent advancements in Microwave Engineering including novel techniques in Microwave Antenna Design and various aspects of Microwave Propagation. This book aims to showcase, the various aspects of Communication, Networking, Data Mining, Computational Biology, Bioinformatics, Bio-Statistics and Machine Learning.

In this book, recent trends in Solid State Technologies, VLSI and applicability of modern Electronic Devices in Bio-informatics and Health-Care is focused. Furthermore, this book showcases the modern optimization techniques in Power System Engineering, Machine Design and Power Systems.

This Book highlights the Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Health-Care for day-to-day applications.

Societal benefits of Microwave Technologies for smooth and hustle-free life are also areas of major focus. Microwave Engineering includes recent advancements and novel techniques in Microwave Antenna Design and various aspects of Microwave Propagation.

Day-to-Day applicability of modern communication and networking technologies are a matter of prime concern. This book aims to showcase, the various aspects of Communication, Networking, Data Mining, Computational Biology, Bioinformatics, Bio-Statistics and Machine Learning.

Role of Solid Sate Engineering in development of modern electronic gadgets are discussed. In this book, recent trends in Solid State Technologies, VLSI and applicability of modern Electronic Devices in Bio-informatics and Biosensing Devices for Smart Health care are also discussed.

Features:

This book focuses on an eminent technology called next generation sequencing (NGS) which has entirely changed the procedure of examining organisms and will have a great impact on biomedical research and disease diagnosis. Numerous computational challenges have been brought on by the rapid advancement of large-scale next-generation sequencing (NGS) technologies and their application. The term ""biomedical imaging"" refers to the use of a variety of imaging techniques (such as X-rays, CT scans, MRIs, ultrasounds, etc.) to get images of the interior organs of a human being for potential diagnostic, treatment planning, follow-up, and surgical purposes. In these circumstances, deep learning, a new learning method that uses multi-layered artificial neural networks (ANNs) for unsupervised, supervised, and semi-supervised learning, has attracted a lot of interest for applications to NGS and imaging, even when both of these data are used for the same group of patients.

The three main research phenomena in biomedical research are disease classification, feature dimension reduction, and heterogeneity. AI approaches are used by clinical researchers to efficiently analyse extremely complicated biomedical datasets (e.g., multi-omic datasets. With the use of NGS data and biomedical imaging of various human organs, researchers may predict diseases using a variety of deep learning models. Unparalleled prospects to improve the work of radiologists, clinicians, and biomedical researchers, speed up disease detection and diagnosis, reduce treatment costs, and improve public health are presented by using deep learning models in disease prediction using NGS and biomedical imaging. This book influences a variety of critical disease data and medical images.

This book looks at the integration of blockchain technology in healthcare settings, focusing on its potential to address security and privacy concerns of medical applications. From fragmented electronic health records (EHRs) to data breaches and interoperability issues, innovative solutions are necessary to unlock the full potential of health information and prevent the recurrence of such issues.

Blockchain offers a promising framework for addressing these challenges. Its decentralized, tamper-resistant nature holds the key to building trust and transparency in healthcare data management. By leveraging blockchain technology, secure, interoperable systems empower patients to take control of their health information while facilitating a seamless collaboration among healthcare providers. Throughout this book, the authors explore the fundamental principles of blockchain technology and its applications within the healthcare landscape. From EHRs and patient consent management to pharmaceutical supply chains and clinical research, this book examines how blockchain can drive efficiency, enhance security, and ultimately improve patient outcomes.

This book is intended for a broad audience, including healthcare professionals, patients, policymakers, and anyone interested in the intersection of technology and healthcare.

This book looks at the integration of blockchain technology in healthcare settings, focusing on its potential to address security and privacy concerns of medical applications. From fragmented electronic health records (EHRs) to data breaches and interoperability issues, innovative solutions are necessary to unlock the full potential of health information and prevent the recurrence of such issues.

Blockchain offers a promising framework for addressing these challenges. Its decentralized, tamper-resistant nature holds the key to building trust and transparency in healthcare data management. By leveraging blockchain technology, secure, interoperable systems empower patients to take control of their health information while facilitating a seamless collaboration among healthcare providers. Throughout this book, the authors explore the fundamental principles of blockchain technology and its applications within the healthcare landscape. From EHRs and patient consent management to pharmaceutical supply chains and clinical research, this book examines how blockchain can drive efficiency, enhance security, and ultimately improve patient outcomes.

This book is intended for a broad audience, including healthcare professionals, patients, policymakers, and anyone interested in the intersection of technology and healthcare.

Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medical diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep learning (DL) techniques are widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. However, accuracy and reliability in model performance can be a concern in tackling data generated from medical images and signals, making it challenging for researchers and practitioners. Therefore, optimized models can produce quality healthcare services to handle the complexities involved in biomedical research.

Various optimization techniques have been employed to optimize parameters, hyper-parameters, and architectural information of ML/DL models explicitly applied to biological, medical, and signal data. The swarm intelligence approach has the potential to solve complex non-linear optimization problems. It mimics the collective behavior of social swarms such as ant colonies, honey bees, and bird flocks. The cooperative nature of swarms can search global settings of ML/DL models, which efficiently provide the solution to biomedical engineering applications. Finally, the book aims to provide the utility of swarm optimization and similar optimization techniques to design ML/DL models to improve the solutions related to biomedical engineering.

Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medical diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep learning (DL) techniques are widely used in biomedical engineering to develop intelligent decision-making healthcare systems in real-time. However, accuracy and reliability in model performance can be a concern in tackling data generated from medical images and signals, making it challenging for researchers and practitioners. Therefore, optimized models can produce quality healthcare services to handle the complexities involved in biomedical research.

Various optimization techniques have been employed to optimize parameters, hyper-parameters, and architectural information of ML/DL models explicitly applied to biological, medical, and signal data. The swarm intelligence approach has the potential to solve complex non-linear optimization problems. It mimics the collective behavior of social swarms such as ant colonies, honey bees, and bird flocks. The cooperative nature of swarms can search global settings of ML/DL models, which efficiently provide the solution to biomedical engineering applications. Finally, the book aims to provide the utility of swarm optimization and similar optimization techniques to design ML/DL models to improve the solutions related to biomedical engineering.