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This book presents the select proceedings of the International Symposium entitled “Materials of the Millennium: Emerging Trends and Future Prospects” (MMETFP 2021). It discusses the synthesis, tailoring, and characterization of different materials for functional applications in various sectors which include but not limited to energy, environment, biomedical/ health care, construction, transportation etc. Topics covered in this book are synthesis and characterization of polymers, ceramics, composites, biomaterials, carbon-based nanostructures as well as materials for green environment, structural materials, modeling and simulation of materials. The book also covers the topic of emerging trends in nanostructured materials, thin films, and devices. The book is useful for students, researchers, and professionals working in the various areas of materials science and engineering.
Data-driven science has become a major decision-making aid for the diagnosis and treatment of disease. Computational and visual analytics enables effective exploration and sense making of large and complex data through the deployment of appropriate data science methods, meaningful visualisation and human-information interaction. This edited volume covers state-of-the-art theory, method, models, design, evaluation and applications in computational and visual analytics in desktop, mobile and immersive environments for analysing biomedical and health data. The book is focused on data-driven integral analysis, including computational methods and visual analytics practices and solutions for discovering actionable knowledge in support of clinical actions in real environments. By studying how data and visual analytics have been implemented into the healthcare domain, the book demonstrates how analytics influences the domain through improving decision making, specifying diagnostics, selecting the best treatments and generating clinical certainty.
Data analysis plays a vital role in guiding medical treatment plans, patient care, and the formulation of control and prevention policies in the field of healthcare. In today's era, researchers in these domains require a firm grasp of data, statistical concepts, and programming skills due to the increasing complexity of data. Reproducible analyses and cutting-edge statistical methods are becoming increasingly necessary. This book, which is both comprehensive and highly practical, addresses these challenges by laying a solid foundation of data and statistical theory for readers. Subsequently, it equips them with practical skills to conduct analyses using the powerful R programming language, w...
Vols. 1- contain separately paged sections Journal & summaries, Acts and notifications, and Reports.
In the era of 'Algorithmic Medicine', the integration of Artificial Intelligence (AI) in healthcare holds immense potential to address critical challenges faced by the industry. Drawing upon the expertise and experience of the authors in medicine, data science, medical informatics, administration, and entrepreneurship, this textbook goes beyond theoretical discussions to outline practical steps for transitioning AI from the experimental phase to real-time clinical integration. Using the Translational Science methodology, each chapter of the book concisely and clearly addresses the key issues associated with AI implementation in healthcare. Covering technical, clinical, ethical, regulatory, and legal considerations, the authors present evidence-based solutions and frameworks to overcome these challenges. Engaging case studies and a literature review of peer-reviewed studies and official documents from reputed organizations provide a balanced perspective, bridging the gap between AI research and actual clinical practice.
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