Haipeng Liu - Böcker

This book provides a comprehensive overview of cutting-edge technologies in the diagnosis of multiple cardiovascular disease. Readers will understand technical advancements and research gaps, which will help them to optimize the design of algorithms and devices.Cutting-Edge Diagnostic Technologies in Cardiovascular Diseases: Towards Data-Driven Smart Healthcare provides details on the adoption and implementation of advanced diagnostic techniques in different clinical settings, including population screening, clinical diagnosis, risk prediction, data-driven diagnosis, and remote healthcare monitoring. It also covers various cardiovascular diseases, from the macrovascular to microvascular levels, where early and accurate diagnosis is a high clinical need, for example, stroke, intracranial atherosclerosis, coronary artery disease, and microvascular dysfunction. The book is a practical guide with case studies, and the authors cover a wide range of cutting-edge diagnostic techniques, including artificial intelligence, radiological imaging, wearable sensors, genetic biomarkers, and multi-omics data integration. It summarizes the potentials, challenges, and ethical concerns in the implementation of these techniques under current clinical settings. It also discusses the future directions and perspectives for next-generation diagnostics based on AI-enhanced multimodal data fusion.This book targets a mixed audience of data scientists, engineers, clinicians, researchers, academics, and students interested in cutting-edge technologies, methodologies, and practices in the diagnostics of cardiovascular diseases to resolve the challenging gaps in healthcare and clinical applications.

This book offers an in-depth exploration of how innovative technologies are reshaping the landscape of cancer diagnosis, treatment, and care by examining the intersection of precision medicine, digital health, and disruptive scientific advances in oncology and focusing on the integration of molecular profiling, artificial intelligence, and digital health infrastructures to revolutionize cancer care. Through 15 detailed chapters, the book covers a range of cutting-edge topics, including the application of AI and deep learning in oncologic imaging, the rise of liquid biopsy techniques for non-invasive cancer detection, and the powerful synergy of radiogenomics in personalizing patient treatment. It delves into how multi-omics integration and systems biology are being leveraged to understand tumor biology better, predict disease progression, and identify novel therapeutic targets. The book also addresses the evolving role of AI in predictive modeling and decision support systems, providing clinicians with advanced tools for risk stratification and prognostic analysis. It explores the ethical and regulatory challenges of integrating digital technologies into clinical practice and offers a global perspective on the barriers to equitable access in cancer care. Designed for oncologists, researchers, data scientists, biomedical engineers, and healthcare professionals, Precision Digital Oncology bridges the gap between cutting-edge research and real-world application, providing a comprehensive, forward-looking roadmap for the future of cancer treatment. Whether you're exploring the impact of AI in cancer care or seeking insights into the future of digital health technologies, this book offers critical knowledge for anyone interested in the next generation of cancer research and therapeutic strategies.

As such, the proposed book serves as an indispensable resource for healthcare professionals, data scientists, researchers, and anyone invested in the future of healthcare and AI.

This book serves as a critical resource that bridges the gap between burgeoning technology and its practical implementation. The book starts with an in-depth exploration of healthcare 5.0 principles, laying the foundation for the reader to understand the current shifts in healthcare paradigms. Then, it dives into the intricacies of generative models in healthcare, detailing how these algorithms work and the applications they serve. The book further delves into the subsets of generative machine learning and deep learning techniques in healthcare. As we move towards more complex applications, the book takes a turn to address the critical subject of interpretability and explainability in generative models, a topic that resonates profoundly given the life-critical nature of medical decisions. Finally, the book concludes with a robust discussion on the security and privacy concerns that accompany the deployment of GAI in real healthcare settings. By offering a multidimensional viewpoint—coupled with case studies, statistical analyses, and expert insights—the book ensures that the reader is left with a nuanced understanding of how GAI can be both a boon and a challenge in healthcare. As such, the proposed book serves as an indispensable resource for healthcare professionals, data scientists, researchers, and anyone invested in the future of healthcare and AI.

This book is considered as an essential medium to introduce the up-to-date findings, new level research, and developing fields in the area of technology and computing for First International Conference on Emerging Technologies and Computing Innovations (ICETCI-2025). The objective of the ICETCI-2025 is to provide a platform to highlight state-of-the-art research work and innovative findings in technology and computing. The conference is focused on filling the gap between modern theoretical improvements and real-life issues by providing a platform for discussions among experts in different areas concerning innovative fields like AI, ML, big data, blockchain, IoT giant computing, etc. ICETCI-2025 benefits from being a multidisciplinary approach for a broad set of emerging technologies. The conference aims to foster the exchange of ideas and experiences by bringing together leaders, researchers, academics, industry practitioners as well as policymakers. Much of the diversity they provide aids unconventional thinking, applicable implementation, and strategic growth that tackles current as well as future technology hurdles. ICETCI-2025 proceedings present high quality research papers, case studies and reviews focusing on state of the art developments in domains like artificial intelligence, big data analytics, cybersecurity and privacy, IoT and blockchain and cloud computing. By collaborating with academia, industry leaders, and policymakers, these proceedings are essential for bringing attention to emerging trends and best practices. They play a critical role in promoting knowledge, stimulating innovation, and providing cross-disciplinary support to help drive technological development. This book is aimed at researchers, academics, graduate students, industry professionals, and policymakers who have an interest in the field of computing, information technologies, and their application.

The book "Advanced wearable sensing in clinical practice towards healthcare 5.0" provides an overview of the state of the art that caters various professionals from clinical, scientific, and engineering backgrounds, as well as the novices that are interested in wearable sensing technology. It presents a comprehensive overview of modern wearable technology and unmet challenges. The book covers research hotspots in wearable technology, including advanced materials, low-cost wearable sensing systems, bio-signal processing, multimodal data analysis, artificial intelligence, and internet-of-medical-things. The readers from various research backgrounds (e.g., biomedical engineering, artificial intelligence, material sciences, etc.) can get an in-depth understanding of current trends and future directions. It summarizes different technologies regarding the clinical needs, theoretical basis, latest technical innovations, challenges in implementation, and limitations. These details will help improve existing designs and algorithms to cater different application scenarios. The book also provides the details of the implementation of advanced wearable sensors in different clinical settings including population screening, clinical diagnosis, to remote healthcare monitoring. The targeted diseases include cardiovascular, neurological, respiratory, metabolic, and other chronic diseases. By analyzing relevant standards and regulations, the challenges for next-generation wearable sensors are discussed in the context of healthcare ecosystem from a perspective of healthcare 5.0. In summary, the book focus on technical innovations but also delves into clinical and regulatory aspects. It caters a broad spectrum of readers. Clinical researchers, healthcare professionals, and students can obtain a better grasp of current trends of wearable technology. Biomedical engineers can understand the clinical needs, the state of the art, and the challenges in implementation, to develop better wearable sensors and algorithms for signal processing and data analysis. Public health researchers and policymakers can update the regulations and clinical guidelines to enable the integration of advanced wearable sensing technologies into current healthcare ecosystems.

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.