Synopsis
The integration of the Internet of Things (IoT) and Machine Learning (ML) is revolutionizing healthcare and environmental management by enabling real-time monitoring, predictive analytics, and personalized interventions. These technologies enhance patient care by facilitating early disease detection, remote monitoring, and data-driven treatment strategies, ultimately improving health outcomes. In environmental management, IoT and ML contribute to sustainable solutions by tracking air and water quality, predicting pollution trends, and optimizing resource usage. Their application in decentralized health records and chronic disease management streamlines operations, reduces costs, and empowers individuals with greater control over their health. As these technologies continue to evolve, they hold immense potential to create smarter, more resilient healthcare and environmental systems. Next-Generation Therapeutics Using Internet of Things and Machine Learning provides a comprehensive framework for understanding and implementing IoT and ML in healthcare and environmental monitoring. By exploring practical applications, this book delves into how these technologies are reshaping diagnostics, patient care, operational efficiencies, and environmental sustainability. Covering topics such as artificial intelligence (AI), medical data exchange, and sustainability, this book is an excellent resource for researchers, practitioners, students, and more.
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About the Author
Mohammed Shuaib, recognized in the World's Top 2% Scientists Ranking 2024 (by Stanford University), specializes in blockchain, IoT, cybersecurity, and machine learning applications in engineering. He holds a PhD in Computer Engineering from Universiti Teknologi Malaysia (UTM). With an h-index of 26, over 1750 citations, and 4 patents, Dr. Shuaib is a prolific researcher with more than 58 publications in ISI-ranked and Scopus-indexed journals, alongside 25 conference papers. His expertise spans machine learning, AI-driven optimizations, and sustainable development, with a focus on applying AI techniques such as artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and reinforcement learning (RL) across engineering disciplines. Dr. Shuaib's editorial experience includes serving as Associate Editor for Sustainable Computing: Informatics and Systems (Elsevier) and contributing to editorial boards of journals like PLOS ONE, Wiley, IAES, IGI Global, and Discover Internet of Things (Springer). His editorial roles, coupled with his membership in professional organizations such as IEEE, ACM, and IAENG, highlight his leadership in advancing research in his areas of expertise.
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Hardcover. Condition: new. Hardcover. The integration of the Internet of Things (IoT) and Machine Learning (ML) is revolutionizing healthcare and environmental management by enabling real-time monitoring, predictive analytics, and personalized interventions. These technologies enhance patient care by facilitating early disease detection, remote monitoring, and data-driven treatment strategies, ultimately improving health outcomes. In environmental management, IoT and ML contribute to sustainable solutions by tracking air and water quality, predicting pollution trends, and optimizing resource usage. Their application in decentralized health records and chronic disease management streamlines operations, reduces costs, and empowers individuals with greater control over their health. As these technologies continue to evolve, they hold immense potential to create smarter, more resilient healthcare and environmental systems. Next-Generation Therapeutics Using Internet of Things and Machine Learning provides a comprehensive framework for understanding and implementing IoT and ML in healthcare and environmental monitoring. By exploring practical applications, this book delves into how these technologies are reshaping diagnostics, patient care, operational efficiencies, and environmental sustainability. Covering topics such as artificial intelligence (AI), medical data exchange, and sustainability, this book is an excellent resource for researchers, practitioners, students, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798337310220
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