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Science in Medicine: From Authoritative Opinion through Evidence-Based Medicine to Big Data & Beyond
Dennis J. Mazur
€ 304.32
€ 224.05
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Description for Science in Medicine: From Authoritative Opinion through Evidence-Based Medicine to Big Data & Beyond
Hardback. Num Pages: 347 pages. BIC Classification: MF. Dimension: 260 x 180. .
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 recognising 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 recognise 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.
Product Details
Format
Hardback
Publication date
2015
Publisher
Nova Science Publishers Inc United States
Number of pages
347
Condition
New
Number of Pages
347
Place of Publication
New York, United States
ISBN
9781634836838
SKU
V9781634836838
Shipping Time
Usually ships in 5 to 9 working days
Ref
99-2
About Dennis J. Mazur
Dr Mazur completed his BA, MA, MD, PhD at Stanford University; Dr. Mazur completed his residency in medicine and fellowship at Stanford University Medical School. Dr. Mazur has presented his research at the European Association for the Study of Science and Technology Conference on Public Proofs (Paris, France); (European Society for Medical Decision Making (Lille, France; Marburg, Germany; Taormina, Sicily), International Symposium of Forecasting (Stockholm, Sweden), Society for Medical Decision Making, and Society for General Internal Medicine, among others. Dr. Mazur's research on the history of probability is published in the journal Medical Decision Making. Dr. Mazur's work on the history of Big Data in surgery is published appeared in the journal Big Data and Society. Dr. Mazur has served as Professor of Medicine, Oregon Health and Science University; he has served as Senior Scholar, Center for Ethics in Health Care (OHSU), and he has served as Feature Editor of the journal Medical Decision Making. Dr. Mazur has served as a peer-reviewer for the journals: Annals of Internal Medicine, British Medical Journal, Canadian Medical Association Journal, Journal of the American Medical Association, New England Journal of Medicine, among others.
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