Effectively coversthe essentials of allied health chemistry without excessive andunnecessary detail. Puts chemistry in the context of everyday life.Covers biochemistry thoroughly to allow for flexible treatment andplaces emphasis on its relevance to society. Updates and expandscontent throughout in topics such as DNA, genomics, chemicalmessengers, the new food pyramid, and the modern view of nucleicacid chemistry and protein synthesis. Revises illustrations throughoutfor increased effectiveness. Redesigned diagrams and bulleted lists fora clearer layout.

    It Combines Comprehensive Medical Content With Dynamic New Features And Interactive Technology To Better Support Instructors And To Help Prepare Students For The Field. An Interactive Skills DVD Is Also Packaged Free With Each Copy Of The Text.

    It presents positioning and projection information in an easy-to-read, bulleted format on one side of the page spread, with corresponding positioning photos, radiographic images and anatomical drawings on the other side. Expert content covers pathology, geriatric and pediatric patient populations, survey information, and 100 new positioning photographs for the latest in radiographic positioning. The 6th edition contains a new chapter on digital imaging, and digital imaging information is incorporated where appropriate throughout the book. New photographs and redrawn illustrations create a consistent, visual appearance throughout the book.- Characterized by a clear, easy-to-follow organization that features one projection per page. Positioning and projection information is presented in an easy-to-read bulleted format on the left side of the page, and positioning photos, radiographic images and anatomical drawings are aligned on the right. This show and tell style helps students visualize anatomy and understand positioning.- Includes about 200 of the most commonly requested projections. Competency in performing these projections is necessary for all entry-level practitioners. By contrast, Merrill's Atlas includes over 400 projections and much more information on advanced imaging.- Critique Radiographs provide the basis of classroom or lab discussion. The WB/LM contains questions specific to these radiographs.- Pathologic Indications in appropriate chapters - Introducing pathology with positioning helps students understand the whole patient and improves their ability to produce radiographs that make diagnosis easy for the physician.- Pediatric Applications in appropriate chapters prepare technologists to deal competently with the special needs of their pediatric patients.- Geriatric Applications in appropriate chapters - Important information for technologists to understand the varying needs of their patient base.- Alternative Modalities or procedures inform students of which projections can better demonstrate certain anatomical parts or pathology, or which may be necessary if patient is unable to cooperate fully.- Radiographic Criteria on positioning pages help students develop a routine for evaluating radiographic quality.- Pathology Demonstrated provides students with a larger frame of reference, and therefore a greater understanding, of each projectionA new chapter on digital imaging discusses basic principles, applications, and image quality - digital imaging information essential for making appropriate positioning adjustments - to ensure readers are prepared to encounter new technology in clinical practice.Content updates include a totally new section on surgical radiography, new sections in all chapters on digital imaging considerations, an expanded section on bone densitometry, and a new introduction to positron emission tomography (PET).Updated and revised chapters cover angiography and interventional procedures, and computed tomography.More than 150 new positioning photos, in addition to many updated images, complement the new material.

    Jon C. Thompson presents the latest data in thoroughly updated diagnostic and treatment algorithms for all conditions while preserving the popular at-a-glance table format from the previous edition. You'll get even more art from the Netter Collection as well as new radiologic images that visually demonstrate the key clinical correlations and applications of anatomical imaging. For a fast, memorable review of orthopaedic anatomy, this is a must-have.Maintains the popular at-a-glance table format that makes finding essential information quick and convenient.Contains useful clinical information on disorders, trauma, history, physical exam, radiology, surgical approaches, and minor procedures in every chapter.Lists key information on bones, joints, muscles, and nerves in tables correlate to each Netter image.Highlights key material in different colors-pearls in green and warnings in red-for easy reference. Features both plain film and advanced radiographic (CT and MRI) images, along with cross-sectional anatomic plates for an even more thorough visual representation of the material.Includes additional common surgical approaches to give you a broader understanding of techniques.Incorporates reorganized Complicated Arthology tables for large joints, such as the shoulder, knee, and hip, for increased clarity and to incorporate new artwork and additional clinical correlations.Reflects new data and current diagnostic and treatment techniques through updates to the Disorders and Fractures sections and the Physical Exam and Anatomic tables in each chapter.Presents the very latest developments in the field through thoroughly updated diagnostic and treatment algorithms for all clinical conditions.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    The top-selling CS review book written by students and IMGs who recently passed 100+ high-yield minicases by chief complaint 30 complete cases simulate the exam experience Contains new Patient Encounters, including telephone interviews Perfect for group or solo study YOUR COMPLETE CS SURVIVAL GUIDE FROM THE AUTHORS OF FIRST AID FOR THE USMLE STEP 1 INSIDER ADVICE FOR STEP 2 CS SUCCESS New miniguide shows US students and IMGs how best to use this book Revised by test veterans to reflect the 2005--2006 exam experience Each complete case features standardized patient checklists and a recommended clinical approach Minicases represent the major chief complaints and diagnoses seen on the Step 2 CS Proven strategies for the patient encounter and patient note High-yield, must-know facts on patient diagnosis and workup.

    The author's straightforward approach promotes and reinforces learning on many levels through a wide variety of visual and written exercises. Along with its review of the human body from microscopic to macroscopic levels the workbook also includes practical, clinically oriented activities. KEY TOPICS: The Human Body: An Orientation, Basic Chemistry, Cells and Tissues, Skin and Body Membranes, The Skeletal System, The Muscular System, The Nervous System, Special Senses, The Endocrine System, Blood, The Cardiovascular System, The Lymphatic System and Body Defenses, The Respiratory System, The Digestive System and Body Metabolism, The Urinary System, The Reproductive System. MARKET: For all readers interested in learning the basics of anatomy and physiology.

    It explores the critical concepts while also examining why they are relevant. The core content is presented within the framework of predicting products, proposing mechanisms, and solving synthesis problems. Readers will fine-tune the key skills involved in solving those types of problems with the help of interactive, step-by-step instructions and problems.

    Emphasis is placed upon the theoretical basis of each type of instrument, its optimal area of application, its sensitivity, its precision, and its limitations. The text also introduces students to elementary integrated circuitry, microprocessors and computers, and treatment of analytical data.

    Over 500 clinical photographs and diagrams now illustrate the text, whilst new topics have been added to make the book even more comprehensive. A complementary DVD now accompanies the book, with specially-recorded videos demonstrating many of the clinical examination routines as they are described in the main text. The book is written by a team of editors and contributors who are all active clinicians and experts in their specialist fields, including in general practice where much of clinical teaching is now based. It describes the practical skills which every clinician must acquire and develop in order to evolve diagnostic procedures and management strategies and plans.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    The book concisely reviews key physiological principles and includes clinical correlations throughout to emphasize connections between basic physiology and clinical medicine. Numerous illustrations, tables, and flow charts help students visualize material quickly and aid in long-term retention. End-of-chapter USMLE-style questions and a comprehensive end-of-book exam test the student's problem-solving skills, and clearly explained answers guide the student through the correct steps in reasoning. This edition features increased coverage of pathophysiology, new questions, and a new two-color design and artwork.

    The beginning chapters introduce basic chemical and biological concepts to provide students with the framework they need to comprehend physiological principles. The chapters that follow promote conceptual understanding rather than rote memorization of facts. Health applications are included throughout the book to heighten interest, deepen understanding of physiological concepts, and help students relate the material to their individual career goals. Every effort has been made to help students integrate related concepts and understand the relationships between anatomical structures and their functions.

    is an American Board of Emergency Medicine certified ED doctor. His journey began in the mid-1970s, when he chose to pursue a career in medicine. In his youthful perspective, he came to regard doctors as the good guys, the ones who healed people and saved lives. He knew he’d be one of those good guys one day. Now, with a career spanning more than thirty years, he works as an emergency-room physician in North Carolina. In A License to Heal: Random Memories of an ER Doctor, Bentley describes the real world of emergency medicine from the viewpoint of a practicing physician. This memoir is filled with real-life stories of the ER, including life and death, triumph and tragedy. Meet a man named Solomon Darby, who spoke to long-dead relatives during his own near-death experience. Bentley also recalls the heartbreaking story of a young widow who desperately needed to understand and cope with the death of her husband. Amid the grief, there are also episodes of great humor and human comedy. In the dynamic world of emergency medicine, there is a great deal of pain, blood, and tragedy, but there is also hope, compassion, and excitement—for both the patients and the staff."

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.