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Employing a conversational format and consciously de-emphasizing computational devices, this text focuses instead on the features of experimental design that either clarify or blur p value interpretation, so as to make statistical reasoning accessible to the uninitiated. Through careful, deliberate thought this book provides the non-mathematician with a foundation for understanding the underlying statistical reasoning process in clinical research. It recognizes the inevitable tension between the mathematics of hypothesis testing and the ethical requirements in medical research and concentrates on resolving these issues in p value interpretation.
Intuition is central to discussions about the nature of scientific and philosophical reasoning and what it means to be human. In this bold and timely book, Hillel D. Braude marshals his dual training as a physician and philosopher to examine the place of intuition in medicine. Rather than defining and using a single concept of intuition—philosophical, practical, or neuroscientific—Braude here examines intuition as it occurs at different levels and in different contexts of clinical reasoning. He argues that not only does intuition provide the bridge between medical reasoning and moral reasoning, but that it also links the epistemological, ontological, and ethical foundations of clinical decision making. In presenting his case, Braude takes readers on a journey through Aristotle’s Ethics—highlighting the significance of practical reasoning in relation to theoretical reasoning and the potential bridge between them—then through current debates between regulators and clinicians on evidence-based medicine, and finally applies the philosophical perspectives of Reichenbach, Popper, and Peirce to analyze the intuitive support for clinical equipoise, a key concept in research ethics. Through his phenomenological study of intuition Braude aims to demonstrate that ethical responsibility for the other lies at the heart of clinical judgment. Braude’s original approach advances medical ethics by using philosophical rigor and history to analyze the tacit underpinnings of clinical reasoning and to introduce clear conceptual distinctions that simultaneously affirm and exacerbate the tension between ethical theory and practice. His study will be welcomed not only by philosophers but also by clinicians eager to justify how they use moral intuitions, and anyone interested in medical decision making.
This is a concise book that explains ideas of statistical reasoning for an audience of practising surgeons. It covers topics of specific interest to surgeons, notably concerning patient outcomes after surgery. It uses concrete real examples to illustrate the usefulness of statistical methods.
Learn to evaluate and apply statistics in medicine, medical research, and all health-related fields A Doody's Core Title for 2023! Basic & Clinical Biostatistics provides medical students, researchers, and practitioners with the knowledge needed to develop sound judgment about data applicable to clinical care. This fifth edition has been updated throughout to deliver a comprehensive, timely introduction to biostatistics and epidemiology as applied to medicine, clinical practice, and research. Particular emphasis is on study design and interpretation of results of research. The book features “Presenting Problems” drawn from studies published in the medical literature, end-of-chapter exercises, and a reorganization of content to reflect the way investigators ask research questions. To facilitate learning, each chapter contain a set of key concepts underscoring the important ideas discussed. Features: Key components include a chapter on survey research and expanded discussion of logistic regression, the Cox model, and other multivariate statistical methods Extensive examples illustrate statistical methods and design issues Updated examples using R, an open source statistical software package Expanded coverage of data visualization, including content on visual perception and discussion of tools such as Tableau, Qlik and MS Power BI Sampling and power calculations imbedded with discussion of the statistical model Updated content, examples, and data sets throughout
The Hands-on Guide to Clinical Reasoning in Medicine is the perfect companion to your time on clinical placements, providing an easy-to-read, highly visual guide to help develop your clinical decision making skills, and transfer your knowledge into practice. Packed full of useful tips, key boxes, exercises and summaries that are designed to help you apply the knowledge gained in clinical practice. Divided into the common clinical placements that you would find yourself in: Respiratory, Cardiovascular, Neurology, Geriatrics, Gastroenterology, Nephrology, Endocrinology and Rheumatology, each chapter covers the diagnosis of common clinical conditions, as well as decision-making in their investigation and management. Written for medical students in their clinical years, as well as new doctors and advanced nurse practitioners, The Hands-on Guide to Clinical Reasoning in Medicine provides students with an accessible resource for honing their clinical reasoning skills. Take the stress out of clinical decision making with The Hands-on Guide!
Modern medicine is one of humankind's greatest achievements.Yet today, frequent medical errors and irreproducibility in biomedical research suggest that tremendous challenges beset it. Understanding these challenges and trying to remedy them have driven considerable and thoughtful critical analyses, but the apparent intransigence of these problems suggests a different perspective is needed. Now more than ever, when we see options and opportunities for healthcare expanding while resources are diminishing, it is extremely important that healthcare professionals practice medicine wisely. In Medical Reasoning, neurologist Erwin B. Montgomery, Jr. offers a new and vital perspective. He begins with the idea that the need for certainty in medical decision-making has been the primary driving force in medical reasoning. Doctors must routinely confront countless manifestations of symptoms, diseases, or behaviors in their patients. Therefore, either there are as many different "diseases" as there are patients or some economical set of principles and facts can be combined to explain each patient's disease. The response to this epistemic conundrum has driven medicine throughout history: the challenge is to discover principles and facts and then to develop means to apply them to each unique patient in a manner that provides certainty. This book studies the nature of medical decision making systematically and rigorously in both an analytic and historical context, addressing medicine's unique need for certainty in the face of the enormous variety of diseases and in the manifestations of the same disease in different patients. The book also examines how the social, legal, and economic circumstances in which medical decision-making occurs greatly influence the nature of medical reasoning. Medical Reasoning is essential for those at the intersection of healthcare and philosophy.
The thoroughly updated Second Edition of this highly acclaimed text is a practical, concise, and current guide to diagnosis and treatment of the various diseases that cause dizziness and imbalance. The book progresses from symptoms to anatomy and physiology, history and physical examination, laboratory testing, disease entities, and treatment. This edition features expanded coverage of the physical examination and state-of-the-art information on test modalities, imaging techniques, surgical procedures, medical therapies for migraine, and superior canal dehiscence. A companion Website will offer the fully searchable text, a question bank, and videos of physical examination techniques, abnormal eye movements, and surgical techniques. (http://www.goebeldizzypatient.com)
Why is understanding causation so important in philosophy and the sciences? Should causation be defined in terms of probability? Whilst causation plays a major role in theories and concepts of medicine, little attempt has been made to connect causation and probability with medicine itself. Causality, Probability, and Medicine is one of the first books to apply philosophical reasoning about causality to important topics and debates in medicine. Donald Gillies provides a thorough introduction to and assessment of competing theories of causality in philosophy, including action-related theories, causality and mechanisms, and causality and probability. Throughout the book he applies them to important discoveries and theories within medicine, such as germ theory; tuberculosis and cholera; smoking and heart disease; the first ever randomized controlled trial designed to test the treatment of tuberculosis; the growing area of philosophy of evidence-based medicine; and philosophy of epidemiology. This book will be of great interest to students and researchers in philosophy of science and philosophy of medicine, as well as those working in medicine, nursing and related health disciplines where a working knowledge of causality and probability is required.
Since its inception in World War II, the clinical trial has evolved into a standard procedure in determining therapeutic efficacy in many Western industrial democracies. Its features include a "control" group of patients that do not receive the experimental treatment, the random allocation of patients to either the experimental or control group, and the use of blind assessment so that the researchers do not know which patients are in either group. Even though it has been only within the past generation that the clinical trial has moved to the forefront of medical research, comparative statistics in a therapeutic context has a much longer history. From that history J. Rosser Matthews chooses to discuss three crucial debates: that among clinicians before the Parisian Academy of Medicine in 1837, the debate in the German physiological literature during the 1850s, and, in the early twentieth century, the debate over the bacteriologist's diagnostic technique involving the "opsonic index." Matthews demonstrates that despite the very real differences separating clinician, physiologist, and bacteriologist, they all shared an antipathy toward the methods of the statistician. Since they viewed medical judgment as a form of "tacit knowledge," they downplayed the concerns of the medical statistician who was attempting to make medical inference into something explicit and quantitative. Only when "medical decision-making" moved from the cloistered confines of professional medical expertise into the arena of open political debate could the medical statistician (and the clinical trial) gain the upper hand.
Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".