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This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.
Stem Cells and Biomaterials for Regenerative Medicine addresses the urgent need for a compact source of information on both the cellular and biomaterial aspects of regenerative medicine. By developing a mutual understanding between three separately functioning areas of science—medicine, the latest technology, and clinical economics—the volume encourages interdisciplinary relationships that will lead to solutions for the significant challenges faced by today's regenerative medicine. Users will find sections on the homeostatic balance created by apoptosis and proliferating tissue stem cells, the naturally regenerative capacities of various tissue types, the potential regenerative benefits of iPS-generation, various differentiation protocols, and more. Written in easily accessbile language, this volume is appropriate for any professional or medical staff looking to expand their knowledge with regard to stem cells and regenerative medicine. - Arms readers with key information on tissue engineering, artificial organs and biomaterials, while using broadly accessible language - Provides broad introduction to, and examples of, various types of stem cells, core concepts of regenerative medicine, biomaterials, nanotechnology and nanomaterials, somatic cell transdyferentiation, and more - Edited and authored by researchers with expertise in regenerative medicine, (cancer) stem cells, biomaterials, genetics and nanomaterials
Cell Polarity in Development and Disease offers insights into the basic molecular mechanisms of common diseases that arise as a result of a loss of ordered organization and intrinsic polarity. Included are diseases affecting highly polarized epithelial tissues in the lung and kidney, as well as loss and gain of cell polarity in the onset and progression of cancer. This book provides a basic resource for understanding the biology of polarity, offering a starting point for those thinking of targeting cell polarity for translational medical research. - Provides basic science understanding of cell polarity disease and development - Covers diseases affecting polarized epithelial tissues in the lung and kidney, also covering the progression of cancer - Includes historical context of cell polarity research for potential future breakthroughs
This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm. Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology.