Causal Relationships In Medicine
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Causal Relationships In Medicine
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Author : J. Mark Elwood
language : en
Publisher: Oxford University Press, USA
Release Date : 1988
Causal Relationships In Medicine written by J. Mark Elwood and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Language Arts & Disciplines categories.
This book shows that in most controversial questions in medicine the essential argument concerns whether the available evidence supports a particular cause-and-effect relationship. Making this evaluation, however, requires a degree of critical thinking that is not emphasized in medical education. In redressing this imbalance, the author demonstrates that by defining the postulated causal relationship, the possible causal and non-causal explanations can be considered in a logical and constructive manner. Elwood assumes no preliminary knowledge, but starts from a simple logical base to lead the reader through types of studies which are relevant, including the issue of selection in subjects, bias in observations, influences of other factors, and statistical analysis. This yields a question and answer approach that can be applied to a wide range of clinical and epidemiological issues.
Discovery And Representation Of Causal Relationships From A Large Time Oriented Clinical Database The Rx Project
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Author : R. L. Blum
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-12
Discovery And Representation Of Causal Relationships From A Large Time Oriented Clinical Database The Rx Project written by R. L. Blum and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-12 with Medical categories.
As a hospital physician it is impossible to escape the notion that the difficult medical problems one encounters are also being confronted by other' physicians throughout the world. It is equally apparent that without special effort one's own patient observations will not be shared with others. Without the medical literature there would be almost no meaningful shadng of experience. Medical textbooks and journals contain reports of the latest tests and treatments. from university hospitals and research centers. There are, however, definite limitations to the medical literature. First. the literature records only a miniscule and highly select portion of medical experience. Second, because of this selectivity, it may be difficult to apply the findings and recommendations in the literature to one's own patients. One serious consequence of these characteristics of the medical literature is that patients are largely overtreated. Tests and treatments are over-prescribed, and adverse effe
Discovery And Representation Of Causal Relationships From A Large Time Oriented Clinical Database
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Author : Robert L. Blum
language : en
Publisher: Springer
Release Date : 1982
Discovery And Representation Of Causal Relationships From A Large Time Oriented Clinical Database written by Robert L. Blum and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982 with Automatic hypothesis formation categories.
Critical Appraisal Of Epidemiological Studies And Clinical Trials
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Author : Mark Elwood
language : en
Publisher: OUP Oxford
Release Date : 2007-02-22
Critical Appraisal Of Epidemiological Studies And Clinical Trials written by Mark Elwood and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-02-22 with Medical categories.
This book presents a logical system of critical appraisal, to allow readers to evaluate studies and to carry out their own studies more effectively. This system emphasizes the central importance of cause and effect relationships. Its great strength is that it is applicable to a wide range of issues, and both to intervention trials and observational studies. This system unifies the often different approaches used in epidemiology, health services research, clinical trials, and evidence-based medicine, starting from a logical consideration of cause and effect. The author's approach to the issues of study design, selection of subjects, bias, confounding, and the place of statistical methods has been praised for its clarity and interest. Systematic reviews, meta-analysis, and the applications of this logic to evidence-based medicine, knowledge-based health care, and health practice and policy are discussed. Current and often controversial examples are used, including screening for prostate cancer, publication bias in psychiatry, public health issues in developing countries, and conflicts between observational studies and randomized trials. Statistical issues are explained clearly without complex mathematics, and the most useful methods are summarized in the appendix. The final chapters give six applications of the critical appraisal of major studies: randomized trials of medical treatment and prevention, a prospective and a retrospective cohort study, a small matched case-control study, and a large case-control study. In these chapters, sections of the original papers are reproduced and the original studies placed in context by a summary of current developments.
Rethinking Causality Complexity And Evidence For The Unique Patient
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Author : Rani Lill Anjum
language : en
Publisher: Springer Nature
Release Date : 2020-06-02
Rethinking Causality Complexity And Evidence For The Unique Patient written by Rani Lill Anjum and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-02 with Philosophy categories.
This open access book is a unique resource for health professionals who are interested in understanding the philosophical foundations of their daily practice. It provides tools for untangling the motivations and rationality behind the way medicine and healthcare is studied, evaluated and practiced. In particular, it illustrates the impact that thinking about causation, complexity and evidence has on the clinical encounter. The book shows how medicine is grounded in philosophical assumptions that could at least be challenged. By engaging with ideas that have shaped the medical profession, clinicians are empowered to actively take part in setting the premises for their own practice and knowledge development. Written in an engaging and accessible style, with contributions from experienced clinicians, this book presents a new philosophical framework that takes causal complexity, individual variation and medical uniqueness as default expectations for health and illness.
Practical Approaches To Causal Relationship Exploration
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Author : Jiuyong Li
language : en
Publisher: Springer
Release Date : 2015-03-02
Practical Approaches To Causal Relationship Exploration written by Jiuyong Li and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-02 with Computers categories.
This brief presents four practical methods to effectively explore causal relationships, which are often used for explanation, prediction and decision making in medicine, epidemiology, biology, economics, physics and social sciences. The first two methods apply conditional independence tests for causal discovery. The last two methods employ association rule mining for efficient causal hypothesis generation, and a partial association test and retrospective cohort study for validating the hypotheses. All four methods are innovative and effective in identifying potential causal relationships around a given target, and each has its own strength and weakness. For each method, a software tool is provided along with examples demonstrating its use. Practical Approaches to Causal Relationship Exploration is designed for researchers and practitioners working in the areas of artificial intelligence, machine learning, data mining, and biomedical research. The material also benefits advanced students interested in causal relationship discovery.
Stats Con
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Author : James Penston
language : en
Publisher:
Release Date : 2010
Stats Con written by James Penston and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematics categories.
About Stats.con - How we've been fooled by statistics-based research in medicine: Statistics-based research is the method by which the causes of disease and the effectiveness of new treatments are investigated. Epidemiological studies and large-scale randomised controlled trials dominate medical research. Judged by the number of papers published each year, this type of research would appear to be a success. Yet it s a triumph of appearance over substance. We ve been cajoled into believing that great advances in medicine have occurred when, in fact, this isn t the case. Large RCTs are placed at the summit of the hierarchy of evidence and are claimed to be the most reliable means of establishing causal relationships in medical research. They are highly complex structures designed to identify small differences in outcome between the active treatment group and controls. But how do we know that the observed difference is caused by the drug? Proponents of RCTs assert that the method excludes alternative explanations namely, the unequal distribution of other causal factors, bias in the assessment of the outcome and chance. In other words, they believe that these studies have internal validity. The primary thesis of stats.con is that the grounds for causal inference in statistics-based research are lacking. Firstly, the components of the RCT including randomisation, allocation concealment, double-blind administration of treatment, the handling of withdrawals and drop-outs, and the statistical tests don t guarantee that the conditions for internal validity have been satisfied. Secondly, the frequentist approach to statistics, which continues to be used in almost all medical research studies despite being subjected to serious criticisms in recent years, is unsound. Thirdly, and most importantly, the inference from a small difference in outcome to the presence of a causal relationship is highly questionable. Given these arguments, it s of some importance to note that neither the results of individual RCTs nor the statistical method in general can be tested independently. This is an inevitable consequence of the subject matter of this type of research which involves heterogeneous samples with unknown mixtures of constituents. The inability to test the results of statistics-based research is of particular concern as fraud is more common than hitherto supposed in medical research. But even if we were to accept the validity of causal inference in this situation and to dismiss concerns about independent testing, we would still face the unpalatable truth that the product of statistics-based research is of little value. The reliability of any generalisation from the results of an individual study to the wider population of patients that is, the external validity is always open to question. We can never know whether the results of a RCT apply to either a particular patient or to a specified group. This is an enormous disadvantage in medicine. But that s not all. The size of the treatment effect in large-scale studies is very small. Indeed, it s so small that the true size of the effect is deliberately hidden by researchers and others with a vested interest in the outcome of the studies. When we look closely, the product of these studies is of dubious worth and doubtful meaning. The reasons for the widespread acceptance of statistics-based research are to be found in the events of the past fifty years or more. History shows how the advocates have used every means at their disposal to spread a flawed methodology and how their views have infiltrated the thinking of generations of researchers, practicing physicians and others involved in the care of patients. But this doesn t apply only to medical research. Many other academic disciplines use similar methods. If, as is argued in stats.con, the case against statistics-based research is made, then the implications extend far beyond the field of medicine.
Guiding Principles For Developing Dietary Reference Intakes Based On Chronic Disease
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2017-12-21
Guiding Principles For Developing Dietary Reference Intakes Based On Chronic Disease written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-21 with Medical categories.
Since 1938 and 1941, nutrient intake recommendations have been issued to the public in Canada and the United States, respectively. Currently defined as the Dietary Reference Intakes (DRIs), these values are a set of standards established by consensus committees under the National Academies of Sciences, Engineering, and Medicine and used for planning and assessing diets of apparently healthy individuals and groups. In 2015, a multidisciplinary working group sponsored by the Canadian and U.S. government DRI steering committees convened to identify key scientific challenges encountered in the use of chronic disease endpoints to establish DRI values. Their report, Options for Basing Dietary Reference Intakes (DRIs) on Chronic Disease: Report from a Joint US-/Canadian-Sponsored Working Group, outlined and proposed ways to address conceptual and methodological challenges related to the work of future DRI Committees. This report assesses the options presented in the previous report and determines guiding principles for including chronic disease endpoints for food substances that will be used by future National Academies committees in establishing DRIs.
Causation In Population Health Informatics And Data Science
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Author : Olaf Dammann
language : en
Publisher: Springer
Release Date : 2018-10-29
Causation In Population Health Informatics And Data Science written by Olaf Dammann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-29 with Medical categories.
Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.
Causal Analysis In Biomedicine And Epidemiology
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Author : Mikel Aickin
language : en
Publisher: CRC Press
Release Date : 2001-11-09
Causal Analysis In Biomedicine And Epidemiology written by Mikel Aickin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-11-09 with Mathematics categories.
"Provides current models, tools, and examples for the formulation and evaluation of scientific hypotheses in causal terms. Introduces a new method of model parametritization. Illustrates structural equations and graphical elements for complex causal systems."