Brilliant, outstanding editing work on a very tough and difficult manuscript. My editor put in the additional time that was essential for the best results achievable. I was quite impressed at the effort that went into the editing of this manuscript !!!
Science in Medicine: From Authoritative Opinion through Evidence-Based Medicine to Big Data and BeyondBook Description: In this monograph, we will examine key questions in five areas related to medicine: science, statistics, evidence, Big Data, and the care of patients. First, when and how did science enter medicine? Second, what and how did statistics enter medicine? Third, when did evidence-based medicine begin in medicine and surgery? Fourth, what is Big Data, and how is Big Data different from EBM?Science in Medicine traces the history of science as applied in medicine as that science was developed and continues to develop today as a two-pronged effort: (1) to produce common knowledge for application to human disease and (2) to help, manage, and treat human beings. In the era of diagnosis in the early 1800s, we will view it as the early grounds of a developing evidence-based medicine; the era of recognizing the challenges of disease-related data collections in the early 1600s we will view as the early grounds capturing many of the challenges of what is now referred to as the era of Big Data. We will focus on each era of medicine and its foundations to better understand where we are today with evidence-based medicine (EBM) and Big Data, and what tomorrow will bring as scientists, mathematicians, physicians, and clinicians jointly work in taking medicine further into the twenty-first century. In all eras, we recognize the importance of developing knowledge about disease and its treatment with the recognition that research even today is not based on a study of the full-range of patients with disease. Therefore, there will always be the need to convince clinicians of whether the knowledge gained by research is solid enough to be applied to the care of the full-range of patients with the disease, or a medical condition that has been researched to some extent such that some knowledge, but not all knowledge gained. Although such knowledge may be based on the study of human research volunteers, the author hopes that it is applicable to the full spectrum of patients including clinician diagnosis, medical therapeutics, surgical devices, and beyond. (Imprint: Nova)Table of Contents: Preface pp. viiChapter 1 Introduction pp. 1-6Chapter 2 An Overview of this History of Evidence in Medicine pp. 7-14Chapter 3 Evidence, Probability, Games of Chance, and Statistics pp. 15-26Chapter 4 Political Arithmetic pp. 27-36Chapter 5 Clinical Case Reports: From Data to Evidence pp. 37-48Chapter 6 The Numerical Method, the Case Study, and the Case Series pp. 49-74Chapter 7 Medical Therapeutics and Proprietary Medicine pp. 75-86Chapter 8 The Prospective Clinical Research Study pp. 87-112Chapter 9 Epidemiology and Clinical Epidemiology pp. 113-114Chapter 10 Evidence-based Medicine pp. 115-136Chapter 11 Clinical Knowledge vs. Research-based Knowledge pp. 137-164Chapter 12 The Scientific Database of Medical Knowledge pp. 165-182Chapter 13 Debiasing Scientific Evidence for Research and Clinical Understanding pp. 183-202Chapter 14 Big Data and Data-intensive Medical Science pp. 203-212Chapter 15 Summary and Conclusions pp. 213-214References pp. 215-244Index pp. 245-253Series: New Developments in Medical Research Binding: Hardcover Pub. Date: 2015 - 4th Quarter Pages: 7x10 - (NBC-C) ISBN: 978-1-63483-683-8 Status: AV
Dennis Mazur received his BA, MA, MD, and PhD from Stanford University.
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