Data Centric Ai Solutions And Emerging Technologies In The Healthcare Ecosystem

The book offers insight into the healthcare system by exploring emerging technologies and AI-based applications and implementation strategies. It includes current developments for future directions as well as covering the concept of the healthcare system along with its ecosystem. Data-Centric AI Solutions and Emerging Technologies in the Healthcare Ecosystem focuses on the mechanisms of proposing and incorporating solutions along with architectural concepts, design principles, smart solutions, decision-making process, and intelligent predictions. It offers state-of-the-art approaches for overall innovations, developments, and implementation of the smart healthcare ecosystem and highlights medical signal and image processing algorithms, healthcare-based computer vision systems, and discusses explainable AI (XAI) techniques for healthcare. This book will be useful to researchers involved in AI, IoT, Data, and emerging technologies in the medical industry. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

The book offers insight into the healthcare system by exploring emerging technologies and AI-based applications and implementation strategies. It includes current developments for future directions as well as covering the concept of the healthcare system along with its ecosystem. Data-Centric AI Solutions and Emerging Technologies in the Healthcare Ecosystem focuses on the mechanisms of proposing and incorporating solutions along with architectural concepts, design principles, smart solutions, decision-making process, and intelligent predictions. It offers state-of-the-art approaches for overall innovations, developments, and implementation of the smart healthcare ecosystem and highlights medical signal and image processing algorithms, healthcare-based computer vision systems, and discusses explainable AI (XAI) techniques for healthcare. This book will be useful to researchers involved in AI, IoT, Data, and emerging technologies in the medical industry. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

This book examines computer vision and IoT-integrated technologies used by medical professionals in decision-making, for sustainable development in a healthcare ecosystem, and to better serve patients and stakeholders. It looks at the methodologies, technologies, models, frameworks, and practices necessary to resolve the challenging issues associated with leveraging the emerging technologies driving the medical field. The chapters discuss machine vision, AI-driven computer vision, machine learning, deep learning, AI-integrated IoT technology, data science, blockchain, AR/VR technology, cloud data, and cybersecurity techniques in designing and implementing a smart healthcare infrastructure in the era of the Industrial Revolution 4.0. Techniques are applied to the detection, diagnosis, and monitoring of a wide range of health issues. Computer Vision and AI-Integrated IoT Technologies in the Medical Ecosystem targets a mixed audience of students, engineers, researchers, academics, and professionals who are researching and working in the field of medical and healthcare industries from different environments and countries.

This book examines computer vision and IoT-integrated technologies used by medical professionals in decision-making, for sustainable development in a healthcare ecosystem, and to better serve patients and stakeholders. It looks at the methodologies, technologies, models, frameworks, and practices necessary to resolve the challenging issues associated with leveraging the emerging technologies driving the medical field. The chapters discuss machine vision, AI-driven computer vision, machine learning, deep learning, AI-integrated IoT technology, data science, blockchain, AR/VR technology, cloud data, and cybersecurity techniques in designing and implementing a smart healthcare infrastructure in the era of the Industrial Revolution 4.0. Techniques are applied to the detection, diagnosis, and monitoring of a wide range of health issues. Computer Vision and AI-Integrated IoT Technologies in the Medical Ecosystem targets a mixed audience of students, engineers, researchers, academics, and professionals who are researching and working in the field of medical and healthcare industries from different environments and countries.

In recent years, the application of Artificial Intelligence (AI) and Internet of Things (IoT) technologies in smart healthcare has been increasing. We are approaching a world where connected smart devices tell people when they need to visit a doctor because these devices will be able to detect health problems and discover symptoms of illness that may need medical care. AI-collaborative IoT technologies can help medical professionals with decision-making. These technologies can also help develop a sustainable and smart healthcare system. AI and IoT Technology and Applications for Smart Healthcare Systems helps readers understand complex scientific topics in a simple and accessible way. It introduces the world of AI-collaborative IoT physics, explaining how this technology behaves at the smallest level and how this can revolutionize healthcare. The book shows how IoT technology and AI can work together to make computers more powerful and capable of solving complex problems in the healthcare sector. Exploring the effect of AI-collaborative technology on IoT technologies, the book discusses how IoT can benefit from AI algorithms to enable machines to learn, make decisions, and process information more efficiently. Because smart machines create more perceptive devices and systems, the application of this technology raises important ethical questions about privacy, security, and the responsible development of healthcare IoT technology, which this book covers. The book also provides insight into the potential applications of these technologies not only in the healthcare industry but also in related fields, such as smart transportation, smart manufacturing, and smart cities.

This book shares new methodologies, technologies, and practices for resolving issues associated with leveraging AI-centric modeling, data analytics, machine learning-aided models, Internet of Things-driven applications, and cybersecurity techniques in the era of Industrial Revolution 4.0. AI-Centric Modeling and Analytics: Concepts, Technologies, and Applications focuses on how to implement solutions using models and techniques to gain insights, predict outcomes, and make informed decisions. This book presents advanced AI-centric modeling and analysis techniques that facilitate data analytics and learning in various applications. It offers fundamental concepts of advanced techniques, technologies, and tools along with the concept of real-time analysis systems. It also includes AI-centric approaches for the overall innovation, development, and implementation of business development and management systems along with a discussion of AI-centric robotic process automation systems that are useful in many government and private industries. This reference book targets a mixed audience of engineers and business analysts, researchers, professionals, and students from various fields.

This book covers the need for Internet of Things (IoT) technologies and artificial intelligence (AI)–aided IoT solutions for business and production. It shows how IoT-based technology uses algorithms and AI models to bring out the desired results. AI-Aided IoT Technologies and Applications for Smart Business and Production shows how a variety of IoT technologies can be used toward integrating data fabric solutions and how intelligent applications can be used to greater effect in business and production operations. The book also covers the integration of IoT data-driven financial technology (fintech) applications to fulfill the goals of trusted AI-aided IoT solutions. Next, the authors show how IoT-based technology uses algorithms and AI models to bring out the desired results across various industries including smart cities, buildings, hospitals, hotels, homes, factories, agriculture, transportation, and more. The last part focuses on AI-aided IoT techniques, data analytics, and visualization tools. This book targets a mixed audience of specialists, analysts, engineers, scholars, researchers, academics, and professionals. It will be useful to engineering officers, IoT and AI engineers, engineering and industrial management students, and research scholars looking for new ideas, methodologies, technologies, models, frameworks, theories, and practices to resolve the challenging issues associated with leveraging IoT technologies, data-driven analytics, AI-aided models, IoT cybersecurity, 5G, sensors, and augmented and virtual reality techniques for developing smart systems in the era of Industrial Revolution 4.0.

While ultra-high field strength diagnosis technologies and artificial intelligence have propelled medicine imaging towards microstructure analysis and precise medicine, persistent challenges remain. These range from long scanning times to motion sensitivity and issues with imaging quality for certain types of tissue. Medical Robotics and AI-Assisted Diagnostics for a High-Tech Healthcare Industry summarizes emerging techniques, outlines clinical applications, and confronts the challenges head-on, proposing avenues for further research. It explores emerging techniques such as human-like robotics, medical Internet of Things (IoT), low-cost CT scanners, portable MRI devices, and breakthroughs in diagnosis technologies like zero echo time (ZTM) and compressed sensing volume interpolation breath-holding test sequences (CS-VIBE). This book provides an overview of the current state of medical imaging and clinical diagnosis applications, then expands into a roadmap for the future, envisioning the seamless integration of medical robotics and AI-assisted applications in the high-tech healthcare industry. As the influence of artificial intelligence continues to grow, the book serves as a clarion call for collaborative efforts, increased research, and unified strategies to navigate the challenges and harness the opportunities presented by the high-tech medical industry. This book is ideal for medical analysts, healthcare scientists, biotechnology analysts, scholars, researchers, academics, professionals, engineers, and students worldwide.