Lalit Mohan Goyal – författare

Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological processes, and treatments, this is an ideal reference.

Machine Learning techniques are used as predictive models for many types of applications, including biomedical applications. These techniques have shown impressive results across a variety of domains in biomedical engineering research. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood, hence the need for new resources and information.

This book reveals the applications of AI and IoT in smart healthcare and medical systems. It provides core principles, algorithms, protocols, emerging trends, security problems, and the latest e-healthcare services findings.The book also provides case studies and discusses how AI and IoT applications such as wireless devices, sensors, and deep learning could play a major role in assisting patients, doctors, and pharmaceutical staff. It focuses on how to use AI and IoT to keep patients safe and healthy and, at the same time, empower physicians to deliver superlative care.This book is written for researchers and practitioners working in the information technology, computer science, and medical equipment manufacturing industry for products and services having basic- and high-level AI and IoT applications. The book is also a useful guide for academic researchers and students.

This book reveals the applications of AI and IoT in smart healthcare and medical systems. It provides core principles, algorithms, protocols, emerging trends, security problems, and the latest e-healthcare services findings.The book also provides case studies and discusses how AI and IoT applications such as wireless devices, sensors, and deep learning could play a major role in assisting patients, doctors, and pharmaceutical staff. It focuses on how to use AI and IoT to keep patients safe and healthy and, at the same time, empower physicians to deliver superlative care.This book is written for researchers and practitioners working in the information technology, computer science, and medical equipment manufacturing industry for products and services having basic- and high-level AI and IoT applications. The book is also a useful guide for academic researchers and students.

This book covers the fundamentals of IoT and healthcare systems for carrying out system architectures, protocols, wearable devices, and interoperability. It explores major challenges in artificial intelligence (AI) and smart computing in resource-constrained IoT-based applications along with cost, energy efficiency, and the availability of quality service.

Healthcare Systems and Health Informatics: Using Internet of Things explores the role of AI and smart computing in health informatics and healthcare with an emphasis on clinical data management and analysis for precise prediction and prompt action. It presents cutting-edge tracking, monitoring, real-time assistance, and security for IoT in healthcare and broadly discusses wearable sensors and IoT devices and their role in smart living assistance. The book goes on to describe a system model and architecture for a clear picture of energy conservation–based IoT in healthcare and explains the challenges and opportunities with IoT-based healthcare industries. A study of the threats and impacts, along with the need for information security, is also included.

The chapters are written by experts in the field, and this book provides a comprehensive description of the important aspects of IoT and health from a beginner- to advanced-level perspective and is ideal for researchers, academicians, students, persons in industry, technologists, and entrepreneurs.

This book covers the fundamentals of IoT and healthcare systems for carrying out system architectures, protocols, wearable devices, and interoperability. It explores major challenges in artificial intelligence (AI) and smart computing in resource-constrained IoT-based applications along with cost, energy efficiency, and the availability of quality service.

Healthcare Systems and Health Informatics: Using Internet of Things explores the role of AI and smart computing in health informatics and healthcare with an emphasis on clinical data management and analysis for precise prediction and prompt action. It presents cutting-edge tracking, monitoring, real-time assistance, and security for IoT in healthcare and broadly discusses wearable sensors and IoT devices and their role in smart living assistance. The book goes on to describe a system model and architecture for a clear picture of energy conservation–based IoT in healthcare and explains the challenges and opportunities with IoT-based healthcare industries. A study of the threats and impacts, along with the need for information security, is also included.

The chapters are written by experts in the field, and this book provides a comprehensive description of the important aspects of IoT and health from a beginner- to advanced-level perspective and is ideal for researchers, academicians, students, persons in industry, technologists, and entrepreneurs.

Ambient assisted living (AAL) utilizes information and communication technology to empower individuals to maintain an active and independent lifestyle for as long as possible. The concept of AAL has been around for decades, but with the evolution of the healthcare sector, we have seen significant advancements in AAL technologies. In recent years, there has been a growing trend towards living alone, and AAL plays a crucial role in supporting individuals to live independently. Ambient Assisted Living (AAL) Technologies: Transitioning from Healthcare 4.0 to Healthcare 5.0 is divided into four comprehensive sections that explore the shift from Healthcare 4.0 to Healthcare 5.0.

It covers AAL technology in the context of Healthcare 4.0 and the Internet of Things (IoT) and fog computing frameworks for real-time applications of natural language processing (NLP) in AAL. The text also delves into advanced artificial intelligence methods for data analytics in AAL, focusing on real-time applications and data analysis for practical use. Additionally, the book covers advanced enabling technologies like blockchain, big data, fog computing and cutting-edge AI techniques for assisted living in Healthcare 5.0. The integration of these technologies and perspectives is crucial for advancing assisted living in the realm of Healthcare 5.0. This book is perfect for students and researchers specializing in AAL and NLP. Professionals working on products for assisted living can also benefit from the valuable insights provided by recent research to improve the efficiency and advancement of their products.

The topic of AAL is already a part of the curriculum in many universities and institutes, and this book will help students explore the various applications of NLP within this field. In addition, individuals looking to engage in innovative projects can find inspiration from the latest advancements in AAL.

Ambient assisted living (AAL) utilizes information and communication technology to empower individuals to maintain an active and independent lifestyle for as long as possible. The concept of AAL has been around for decades, but with the evolution of the healthcare sector, we have seen significant advancements in AAL technologies. In recent years, there has been a growing trend towards living alone, and AAL plays a crucial role in supporting individuals to live independently. Ambient Assisted Living (AAL) Technologies: Transitioning from Healthcare 4.0 to Healthcare 5.0 is divided into four comprehensive sections that explore the shift from Healthcare 4.0 to Healthcare 5.0.

It covers AAL technology in the context of Healthcare 4.0 and the Internet of Things (IoT) and fog computing frameworks for real-time applications of natural language processing (NLP) in AAL. The text also delves into advanced artificial intelligence methods for data analytics in AAL, focusing on real-time applications and data analysis for practical use. Additionally, the book covers advanced enabling technologies like blockchain, big data, fog computing and cutting-edge AI techniques for assisted living in Healthcare 5.0. The integration of these technologies and perspectives is crucial for advancing assisted living in the realm of Healthcare 5.0. This book is perfect for students and researchers specializing in AAL and NLP. Professionals working on products for assisted living can also benefit from the valuable insights provided by recent research to improve the efficiency and advancement of their products.

The topic of AAL is already a part of the curriculum in many universities and institutes, and this book will help students explore the various applications of NLP within this field. In addition, individuals looking to engage in innovative projects can find inspiration from the latest advancements in AAL.

The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data’s immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data.

This book addresses the Internet of Things (IoT), an essential topic in the technology industry, policy, and engineering circles, and one that has become headline news in both the specialty press and the popular media. The book focuses on energy efficiency concerns in IoT and the requirements related to Industry 4.0. It is the first-ever “how-to” guide on frequently overlooked practical, methodological, and moral questions in any nations’ journey to reducing energy consumption in IoT devices.

The book discusses several examples of energy-efficient IoT, ranging from simple devices like indoor temperature sensors, to more complex sensors (e.g. electrical power measuring devices), actuators (e.g. HVAC room controllers, motors) and devices (e.g. industrial circuit-breakers, PLC for home, building or industrial automation). It provides a detailed approach to conserving energy in IoT devices, and comparative case studies on performance evaluation metrics, state-of-the-art approaches, and IoT legislation. 

This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis. The use of prognostic modelling as predictive models to solve complex problems of data mining and analysis in health care is the feature of this book. The book examines the recent technologies and studies that reached the practical level and becoming available in preclinical and clinical practices in computational intelligence.  The main areas of interest covered in this book are highest quality, original work that contributes to the basic science of processing, analysing and utilizing all aspects of advanced computational prognostic modelling in healthcare image and data analysis.

This book focuses on sustainability issues post COVID-19 outbreak, discusses ways to restrict global spread of the pandemic, and also how to survive holistically in the environment. It also discusses the economic impacts on the world due to the coronavirus outbreak. There is a strong need for monitoring and analysis of pandemics for sustainability like epidemic risk analysis by using pattern recognition or the mental health challenges during an outbreak. This book presents ways to find solutions and gives insights to explore innovative methods and predictive modeling techniques, such that masses are prevented from pandemics.​