Molecular Imaging and Targeted Therapy (2版)

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This book, now published in its second edition, covers a wide range of topics relating to the use of radiopharmaceuticals. The basics of nuclear chemistry, radiochemistry, and radiopharmacology are considered in detail, regulatory issues are reviewed, and potential applications in drug development, translational medicine, clinical diagnostics, and targeted therapy are discussed. Compared with the first edition, the chapters on targeted therapy with alpha- and beta-emitting radiopharmaceuticals and theranostics are completely new. Other chapters have been updated and revised as necessary. Radioisotope-based molecular imaging probes (radiopharmaceuticals) provide unprecedented insights into biochemistry and function in both normal and diseased states of living systems, with unbiased in vivo measurements of regional radiotracer activities offering very high specificity and sensitivity. No other molecular imaging technology, including functional magnetic resonance imaging, can provide such high sensitivity and specificity at a tracer level. This book, written by an experienced radiochemist and scientist, offers valuable insights into the full range of applications of this technology.

DEEP LEARNING FOR TARGETED TREATMENTS: TRANSFORMATION IN HEALTHCARE

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DESCRIPTION DEEP LEARNING FOR TREATMENTS The book provides the direction for future research in deep learning in terms of its role in targeted treatment, biological systems, site-specific drug delivery, risk assessment in therapy, etc. Deep Learning for Targeted Treatments describes the importance of the deep learning framework for patient care, disease imaging/detection, and health management. Since deep learning can and does play a major role in a patient’s healthcare management by controlling drug delivery to targeted tissues or organs, the main focus of the book is to leverage the various prospects of the DL framework for targeted therapy of various diseases. In terms of its industrial significance, this general-purpose automatic learning procedure is being widely implemented in pharmaceutical healthcare. Audience The book will be immensely interesting and useful to researchers and those working in the areas of clinical research, disease management, pharmaceuticals, R&D formulation, deep learning analytics, remote healthcare management, healthcare analytics, and deep learning in the healthcare industry.