Pradeep N – författare

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics Unique case study approach provides readers with insights for practical clinical implementation

Unleashing the Potentials of Blockchain Technology for Healthcare Industries discusses blockchain and its adaptation in healthcare industries to provide a secured framework to safeguard healthcare data, both patient and hospital data. The book integrates key pillars of blockchain such as foundations, architecture, smart contracts, adoption, standards, service (BaaS), security, consensus algorithms, drug discovery process, among others, for fortifying the current practices in the healthcare industries. In addition, it offers solutions to the pressing issues currently being faced by the healthcare processes due to the COVD-19 pandemic.

This will be a valuable resource for medical informaticians, researchers, healthcare professionals and members of the biomedical field who are interested in learning more about the potentials of blockchain in healthcare.

Presents comprehensive knowledge on blockchain and its adaptation in healthcare industries Covers a wide spectrum of healthcare areas such as product integrity, drug traceability, patient data management, digital identity management, security and control of healthcare transactions, returned drugs authenticity, pharma supply chain compliance, clinical trials data quality, and reliability Provides an instant reference for beginners to advanced industrial practitioners, researchers and academicians who want to understand the role, impact and challenges of adopting blockchain in healthcare industries

This book comprehensively discusses basic data-driven intelligent systems, the methods for processing the data, and cloud computing with artificial intelligence. It presents fundamental and advanced techniques used for handling large user data, and for the data stored in the cloud. It further covers data-driven decision-making for smart logistics and manufacturing systems, network security, and privacy issues in cloud computing.This book:Discusses intelligent systems and cloud computing with the help of artificial intelligence and machine learning. Showcases the importance of machine learning and deep learning in data-driven and cloud-based applications to improve their capabilities and intelligence. Presents the latest developments in data-driven and cloud applications with respect to their design and architecture. Covers artificial intelligence methods along with their experimental result analysis through data processing tools. Presents the advent of machine learning, deep learning, and reinforcement technique for cloud computing to provide cost-effective and efficient services. The text will be useful for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer engineering, manufacturing engineering, and production engineering.

This book comprehensively discusses basic data-driven intelligent systems, the methods for processing the data, and cloud computing with artificial intelligence. It presents fundamental and advanced techniques used for handling large user data, and for the data stored in the cloud. It further covers data-driven decision-making for smart logistics and manufacturing systems, network security, and privacy issues in cloud computing.This book:Discusses intelligent systems and cloud computing with the help of artificial intelligence and machine learning. Showcases the importance of machine learning and deep learning in data-driven and cloud-based applications to improve their capabilities and intelligence. Presents the latest developments in data-driven and cloud applications with respect to their design and architecture. Covers artificial intelligence methods along with their experimental result analysis through data processing tools. Presents the advent of machine learning, deep learning, and reinforcement technique for cloud computing to provide cost-effective and efficient services. The text will be useful for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer engineering, manufacturing engineering, and production engineering.

INTELLIGENT SYSTEMS FOR REHABILITATION ENGINEERING Encapsulates different case studies where technology can be used as assistive technology for the physically challenged, visually and hearing impaired. Rehabilitation engineering includes the development of technological solutions and devices to assist individuals with disabilities, while also supporting the recovery of the disabled who have lost their physical and cognitive functions. These systems can be designed and built to meet a wide range of needs that can help individuals with mobility, communication, vision, hearing, and cognition. The growing technological developments in machine learning, deep learning, robotics, virtual intelligence, etc., play an important role in rehabilitation engineering. Intelligent Systems for Rehabilitation Engineering focuses on trending research of intelligent systems in rehabilitation engineering which involves the design and development of innovative technologies and techniques including rehabilitation robotics, visual rehabilitation, physical prosthetics, brain computer interfaces, sensory rehabilitation, motion rehabilitation, etc. This groundbreaking book Provides a comprehensive reference covering different computer assistive techniques for the physically disabled, visually and hearing impaired.Focuses on trending research of intelligent systems in rehabilitation engineering which involves the design and development of innovative technologies and techniques.Provides insights into the role of intelligent systems in rehabilitation engineering.Audience Engineers and device manufacturers working in rehabilitation engineering as well as researchers in computer science, artificial intelligence, electronic engineering, who are working on intelligent systems.

Industry 4.0 is revolutionizing the way companies do business by integrating new technologies into workplace practices and into production facilities and throughout their operations. This new volume provides an insightful examination of the role of people analytics—the data-driven and goal-focused method of studying people processes, functions, challenges, and opportunities at work to elevate these systems and achieve sustainable business success—in the era of Industry 4.0. It explores the use of AI and other technologies in analyzing cognition, human potential, and talent management; for studying workplace diversity and inclusion; in performance management and reward analytics; to enhance emotional and social intelligence in decision making; for employee training programs; for employee wellness enhancement; for leadership development; and more.

This book provides a deep dive into how Generative Artificial Intelligence is fostering innovation apart from being impactful, and key problems that affect the healthcare ecosystem as a whole are now being solved. With the rapid rise of Generative Artificial Intelligence (AI), industries are changing rapidly, and healthcare is no exception. Generative AI, as a transformative subset of AI, has the extraordinary ability to create new data, simulate scenarios, and optimize complex processes. Its potential for medical diagnostics and drug development is beyond doubt and it is born to revolutionize medical research and Personalized treatment. Reasoning subtitled Generative AI for Healthcare, this exploratory volume on cutting-edge technology's profound impact on modern medicine is based on years of dedicated research. Key highlights include:·         Using Generative AI to actually produce synthetic teaching sets and consequently re-armed medical-solving equipment will in turn enhance diagnosis and accuracy·         Reducing the amount of time and costs for developing drugs by means of artificial intelligence, by iterating through virtual compounds and simulating molecular environments·         Creating personalized treatment strategies out of specific patient profiles that embrace precision medicine, improving outcomes·         Simulating medical scenarios to measure the effectiveness of a cure in advance expensive, high-risk trials, the profound secrets behind complex diseases are slowly coming to light.This book is designed to help the next generation of healthcare practices address research gaps, regulatory challenges, ethical considerations, and other concerns. Balancing rich case studies with practical insights and forward -looking ideas, this book aims to link up the promise of technological innovation in healthcare with its real application. The book also highlights the need for responsible AI adoption, addressing issues such as data privacy, bias reduction in models, explainable and reliable AI systems. The goal is to provide healthcare professionals, researchers and policy makers with knowledge and tools needed to use Generative AI responsibly and effectively. Whether you are a healthcare provider, AI researcher or industry innovator, Generative AI for Healthcare gives you an essential primer on how AI can be applied to transform patient care outcomes, drive medical research forward -- and even shape the future of healthcare itself.