Monthly, with annual cumulation. Recurring bibliography from MEDLARS data base. Index medicus format. Entries arranged under subject, review, and author sections. Subject, author indexes.

Platelets - winner of a 2013 Highly Commended BMA Medical Book Award for Internal Medicine - is the definitive current source of state-of-the-art knowledge about platelets and covers the entire field of platelet biology, pathophysiology, and clinical medicine. Recently there has been a rapid expansion of knowledge in both basic biology and the clinical approach to platelet-related diseases including thrombosis and hemorrhage. Novel platelet function tests, drugs, blood bank storage methods, and gene therapies have been incorporated into patient care or are in development. This book draws all this information into a single, comprehensive and authoritative resource. - Highly Commended BMA Medical Book Award 2013: Internal Medicine - Comprehensive and definitive source of knowledge about platelets for clinicians, pathologists and scientists - Integrates the entire field of platelet biology, pathophysiology, and clinical medicine - Full color reference comprising 64 chapters, 1400 pages, and 16,000 references - Contributions from 126 world leaders in their fields - New chapters on topics such as the regulation of platelet life span, platelet microRNAs, GPVI and CLEC-2, monitoring of antiplatelet therapy, novel antiplatelet therapy, and making platelets ex vivo

This second edition of Medical Biochemistry is supported by more than 45 years of teaching experience, providing coverage of basic biochemical topics, including the structural, physical, and chemical properties of water, carbohydrates, lipids, proteins, and nucleic acids. In addition, the general aspects of thermodynamics, enzymes, bioenergetics, and metabolism are presented in straightforward and easy-to-comprehend language. This book ties these concepts into more complex aspects of biochemistry using a systems approach, dedicating chapters to the integral study of biological phenomena, including cell membrane structure and function, gene expression and regulation, protein synthesis and post-translational modifications, metabolism in specific organs and tissues, autophagy, cell receptors, signal transduction pathways, biochemical bases of endocrinology, immunity, vitamins and minerals, and hemostasis. The field of biochemistry is continuing to grow at a fast pace. This edition has been revised and expanded with all-new sections on the cell plasma membrane, the human microbiome, autophagy, noncoding, small and long RNAs, epigenetics, genetic diseases, virology and vaccines, cell signaling, and different modes of programmed cell death. The book has also been updated with full-color figures, new tables, chapter summaries, and further medical examples to improve learning and better illustrate the concepts described and their clinical significance. - Integrates basic biochemistry principles with molecular biology and molecular physiology - Illustrates basic biochemical concepts through medical and physiological examples - Utilizes a systems approach to understanding biological phenomena - Fully updated for recent studies and expanded to include clinically relevant examples and succinct chapter summaries

This textbook integrates important mathematical foundations, efficient computational algorithms, applied statistical inference techniques, and cutting-edge machine learning approaches to address a wide range of crucial biomedical informatics, health analytics applications, and decision science challenges. Each concept in the book includes a rigorous symbolic formulation coupled with computational algorithms and complete end-to-end pipeline protocols implemented as functional R electronic markdown notebooks. These workflows support active learning and demonstrate comprehensive data manipulations, interactive visualizations, and sophisticated analytics. The content includes open problems, state-of-the-art scientific knowledge, ethical integration of heterogeneous scientific tools, and procedures for systematic validation and dissemination of reproducible research findings. Complementary to the enormous challenges related to handling, interrogating, and understanding massive amounts of complex structured and unstructured data, there are unique opportunities that come with access to a wealth of feature-rich, high-dimensional, and time-varying information. The topics covered in Data Science and Predictive Analytics address specific knowledge gaps, resolve educational barriers, and mitigate workforce information-readiness and data science deficiencies. Specifically, it provides a transdisciplinary curriculum integrating core mathematical principles, modern computational methods, advanced data science techniques, model-based machine learning, model-free artificial intelligence, and innovative biomedical applications. The book’s fourteen chapters start with an introduction and progressively build foundational skills from visualization to linear modeling, dimensionality reduction, supervised classification, black-box machine learning techniques, qualitative learning methods, unsupervised clustering, model performance assessment, feature selection strategies, longitudinal data analytics, optimization, neural networks, and deep learning. The second edition of the book includes additional learning-based strategies utilizing generative adversarial networks, transfer learning, and synthetic data generation, as well as eight complementary electronic appendices. This textbook is suitable for formal didactic instructor-guided course education, as well as for individual or team-supported self-learning. The material is presented at the upper-division and graduate-level college courses and covers applied and interdisciplinary mathematics, contemporary learning-based data science techniques, computational algorithm development, optimization theory, statistical computing, and biomedical sciences. The analytical techniques and predictive scientific methods described in the book may be useful to a wide range of readers, formal and informal learners, college instructors, researchers, and engineers throughout the academy, industry, government, regulatory, funding, and policy agencies. The supporting book website provides many examples, datasets, functional scripts, complete electronic notebooks, extensive appendices, and additional materials.

Prefaces of textbooks are generally meant to give editors an opportunity to express the rationale for the creation of yet another textbook. It is rare to find an author or editor who does not believe that his/her book fills a very specific need. This editor is no exception. With the incredible proliferation of medical textbooks in recent years, it has become difficult to find an empty niche for yet another text. Nevertheless, the editors and authors of Principles of Medical Therapy in Pregnancy have been impressed by one very clearly appreciated void: While the association of medical disorders with pregnancy is increasing in frequency as improved medical care allows more patients with medical diseases to conceive, an authoritative text covering the issue, comparable to an authoritative text in internal medicine, has been missing. With pregnancy representing a very specific disease situation-different from the nonpregnant state in diagnosis, management, and course of disease-a detailed textbook addressing all these issues for both the internist and the obstetrician seemed urgently needed.

This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression. It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods, placing the new methods in historical context. Author Rand Wilcox includes chapter exercises and many real-world examples that illustrate how various methods perform in different situations. Introduction to Robust Estimation and Hypothesis Testing, Second Edition, focuses on the practical applications of modern, robust methods which can greatly enhance our chances of detecting true differences among groups and true associations among variables. - Covers latest developments in robust regression - Covers latest improvements in ANOVA - Includes newest rank-based methods - Describes and illustrated easy to use software

The revised edition of this renowned and bestselling title is the most comprehensive single text on all aspects of biomaterials science. It provides a balanced, insightful approach to both the learning of the science and technology of biomaterials and acts as the key reference for practitioners who are involved in the applications of materials in medicine. - Over 29,000 copies sold, this is the most comprehensive coverage of principles and applications of all classes of biomaterials: "the only such text that currently covers this area comprehensively" - Materials Today - Edited by four of the best-known figures in the biomaterials field today; fully endorsed and supported by the Society for Biomaterials - Fully revised and expanded, key new topics include of tissue engineering, drug delivery systems, and new clinical applications, with new teaching and learning material throughout, case studies and a downloadable image bank