Human Cancer Diagnosis And Detection Using Exascale Computing
Download Human Cancer Diagnosis And Detection Using Exascale Computing PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Human Cancer Diagnosis And Detection Using Exascale Computing book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Human Cancer Diagnosis and Detection Using Exascale Computing
Human Cancer Diagnosis and Detection Using Exascale Computing The book provides an in-depth exploration of how high-performance computing, particularly exascale computing, can be used to revolutionize cancer diagnosis and detection; it also serves as a bridge between the worlds of computational science and clinical oncology. Exascale computing has the potential to increase our ability in terms of computation to develop efficient methods for a better healthcare system. This technology promises to revolutionize cancer diagnosis and detection, ushering in an era of unprecedented precision, speed, and efficiency. The fusion of exascale computing with the field of oncology has the potential to redefine the boundaries of what is possible in the fight against cancer. The book is a comprehensive exploration of this transformative unification of science, medicine, and technology. It delves deeply into the realm of exascale computing and its profound implications for cancer research and patient care. The 18 chapters are authored by experts from diverse fields who have dedicated their careers to pushing the boundaries of what is achievable in the realm of cancer diagnosis and detection. The chapters cover a wide range of topics, from the fundamentals of exascale computing and its application to cancer genomics to the development of advanced imaging techniques and machine learning algorithms. Explored is the integration of data analytics, artificial intelligence, and high-performance computing to move cancer research to the next phase and support the creation of novel medical tools and technology for the detection and diagnosis of cancer. Audience This book has a wide audience from both computer sciences (information technology, computer vision, artificial intelligence, software engineering, applied mathematics) and the medical field (biomedical engineering, bioinformatics, oncology). Researchers, practitioners and students will find this groundbreaking book novel and very useful.
Federated Learning and Privacy-Preserving in Healthcare AI
The use of artificial intelligence (AI) in data-driven medicine has revolutionized healthcare, presenting practitioners with unprecedented tools for diagnosis and personalized therapy. However, this progress comes with a critical concern: the security and privacy of sensitive patient data. As healthcare increasingly leans on AI, the need for robust solutions to safeguard patient information has become more pressing than ever. Federated Learning and Privacy-Preserving in Healthcare AI emerges as the definitive solution to balancing medical progress with patient data security. This carefully curated volume not only outlines the challenges of federated learning but also provides a roadmap for implementing privacy-preserving AI systems in healthcare. By decentralizing the training of AI models, federated learning mitigates the risks associated with centralizing patient data, ensuring that critical information never leaves its original location. Aimed at healthcare professionals, AI experts, policymakers, and academics, this book not only delves into the technical aspects of federated learning but also fosters a collaborative approach to address the multifaceted challenges at the intersection of healthcare and AI.
Challenges in Information, Communication and Computing Technology
This book explores the critical challenges and emerging trends in Information, Communication, and Computing Technology (ICCT). It provides a comprehensive overview of the key issues facing these rapidly evolving fields, from data security and privacy to advancements in artificial intelligence, communication networks, and quantum computing. Through in-depth analysis and expert perspectives, this volume aims to shed light on the complexities of ICCT and offer innovative solutions for researchers, practitioners, and students. Building on its exploration of challenges in ICCT, this book delves into several core areas. These include the development and deployment of secure and efficient communication networks, the ethical implications and technical hurdles of artificial intelligence and machine learning, and the promise and complexity of quantum computing. The book also addresses the management of big data, highlighting both its potential and the challenges of ensuring data privacy and security. Additionally, it examines the role of sustainability in computing, advocating for greener technologies and practices. The findings presented in this volume emphasize the need for interdisciplinary approaches and innovative thinking to address these challenges, offering insights that are both practical and forward-looking. This book is intended for a diverse audience that includes researchers, practitioners, and students in the fields of Information, Communication, and Computing Technology (ICCT). It is particularly valuable for academics and professionals seeking to deepen their understanding of current challenges and emerging trends in these areas. Additionally, policymakers, industry leaders, and technologists will find the book's insights useful for informing decisions and strategies in the development and implementation of advanced technologies. Whether you are a seasoned expert or a newcomer to the field, this book provides valuable perspectives that can enhance your knowledge and contribute to your work in ICCT. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND)] 4.0 license.