Prashant Upadhyay – författare

Artificial Intelligence (AI) to the Internet of Medical Things (IoMT) is not just a slight enhancement of healthcare but a paradigm shift. Biomedical Applications of AI and IoMT in Smart Healthcare is a pioneering investigation of this change, filling the divide between highly complex computational methods and the practical clinical applications. This volume includes the most promising products to transform modern medicine, based on real-time monitoring of patients and mental health, to early detection of diabetes, hepatitis C, and skin cancers. This book, edited by a renowned group of professionals, Prashant Upadhyay, Pradeep Tomar, Fadi Al-Turjman and Satya Prakash Yadav, is an assemblage of research work around the world that explores practical applications as well as analytical frameworks. The topics addressed in chapters are quite broad, such as AI-based virtual tutors to learn medicine, HOG-based eye-tracking interfaces, hybrid deep learning networks to diagnose melanoma, and optimized neural networks to diagnose diseases. The book is not only focused on the level of sophistication in technology but also on the accessibility, equity, and the health impact on the world. This volume provides a valuable and timely guide to the ecosystem of the IoMT whether you are a researcher, biomedical engineer, health professional or student of digital health technologies. It shows how smart systems are turning healthcare into a more predictive, personalized and pervasive one algorithm at a time. Key Features: Varied Disease Coverage- Covers specialized AI/IoMT models of diabetes, cervical cancer, hepatitis C, monkeypox, melanoma, asthma, blood group classification, demonstrating a wide clinical applicability.Real-World IoMT Integration – A chapters deal with real-time data analysis, patient monitoring, wearable devices, and edge-based fitness coaching with geospatial technology and small language models.State-of-the-art AI and ML Approaches – Shows ensemble, transfer learning (ResNet-50 + SVM), perceptron optimization (Penguin Optimization Algorithm), and HOG-based face landmark detection.International & Multidisciplinary Authorship - The works of various universities and research centers in India, Turkey, and others will be involved, which will guarantee a multinational outlook to the topic of smart healthcare innovation.Bridging Research and Education - Unique focus on AI-powered medical education, virtual tutors, and simulation technologies, which makes it useful in both an academic and clinical training setting.

Digital Health: Managing and Leveraging Health Information Systems offers healthcare professionals, administrators, and technology practitioners a comprehensive, practical understanding of the entire health information system lifecycle—from historical development to future innovation. This volume bridges the critical gap between technical capabilities and clinical utility, providing a clear roadmap for navigating the complexities of digital transformation within the medical landscape. Whether you aim to reform existing systems or launch new digital health initiatives, this book provides the foundational knowledge and strategic foresight needed to make informed decisions that enhance patient outcomes and operational efficiency in both developed and developing healthcare environments.Key FeaturesEnd-to-End Lifecycle Coverage: Covers health information systems from every angle, from their history to how they are governed and implemented, and where they are headed.Core Technology Focus: Provides in-depth examinations of Electronic Health Records (EHR), Health Information Technologies (HIT), and other innovative healthcare solutions driving contemporary delivery models.Practical "Systems Approach": Offers a structured methodology that translates technical capabilities into actionable clinical utility, helping readers bridge theory and practice.Actionable Implementation Guidance: Delivers real-world insights for overcoming common challenges, including information governance, system restructuring, and the integration of advanced digital solutions.Balanced Global Perspective – Addresses the needs of both developed and developing healthcare environments, making it relevant across diverse resource settings.Multidisciplinary Audience Fit: Serves as both an academic reference and a practical guide for healthcare administrators, hospital IT managers, public health policymakers, health informatics students, researchers, and faculty in medical and computer science disciplines.Strategic Decision-Making Tools: Equips readers with the strategic foresight needed for health system reform, digital health strategy design, and adoption of robust information governance frameworks.

This book discusses key concepts such as multi-agent systems, agent communication, and distributed problem-solving. The readers will gain an understanding of how these agents interact within a network, sharing information and resources to make decentralized decisions. The text will also cover the theoretical underpinnings of artificial distributed intelligence, including the principles of distributed computing and the algorithms that facilitate cooperation among agents. This book:Explains how artificial distributed intelligence leverages the coordination and collaboration of multiple autonomous agents to solve complex problems that are beyond the capabilities of a single agent.Key concepts such as multi-agent systems, agent communication, and distributed problem-solving are covered in depth.Provides a thorough exploration of the foundational principles and key concepts of artificial distributed intelligence.Showcases potential risks associated with artificial distributed intelligence, including biases in artificial intelligence algorithms, the implications of autonomous decision-making, and the need for transparency and accountability in artificial intelligence systems.Illustrates advanced topics such as the integration of blockchain and quantum computing with artificial distributed intelligence.This text is written for senior undergraduate students, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and distributed computing.

Artificial Intelligence (AI) and Large Language Models (LLM) are not a thing of the future anymore, but the engines of industrial transformation of the present day. Applications of AI and LLM in Production and Services Industries bridges the gap between leading edge research and practice. This anthology includes the leading scholars of the world to discuss the change in manufacturing floors and even in the customer service centers through the use of AI-driven automation, predictive analytics, and LLM-powered interactions. This book presents a practical roadmap of sustainable growth of businesses by covering smart manufacturing and predictive maintenance, intelligent chatbots and operational efficiency. It does not only deal with technical integration but also with the ethical aspect, cross industry case studies, and future trends. As an industry professional, researcher or technology leader, this book will provide you with the competencies and knowledge to leverage AI and LLMs and gain competitive advantage.Key Features (USPs):Comprehensive Coverage - includes both production (manufacturing, automation) and service (customer experience, healthcare, retail) sectors in a single framework.Real-World Case Studies - Contains practical applications and examples in the world industry and academics.Actionable Insights - Concentrates on how to operate efficiently, predictively, make decisions and be ethical in implementation.Future-Ready Perspective - Discusses the new trends, the development of LLM, and the definite way to adopt AI.Multidisciplinary Expert Contributions - Written by the top researchers and practitioners in the fields of computer science, engineering and business.