Science in Medicine: From Authoritative Opinion through Evidence-Based Medicine to Big Data and Beyond

Author’s review

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A short introduction

Science in Medicine: From Authoritative Opinion through Evidence-Based Medicine to Big Data and Beyond

Book 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. vii

Chapter 1

Introduction

pp. 1-6

Chapter 2

An Overview of this History of Evidence in Medicine

pp. 7-14

Chapter 3

Evidence, Probability, Games of Chance, and Statistics

pp. 15-26

Chapter 4

Political Arithmetic

pp. 27-36

Chapter 5

Clinical Case Reports: From Data to Evidence

pp. 37-48

Chapter 6

The Numerical Method, the Case Study, and the Case Series

pp. 49-74

Chapter 7

Medical Therapeutics and Proprietary Medicine

pp. 75-86

Chapter 8

The Prospective Clinical Research Study

pp. 87-112

Chapter 9

Epidemiology and Clinical Epidemiology

pp. 113-114

Chapter 10

Evidence-based Medicine

pp. 115-136

Chapter 11

Clinical Knowledge vs. Research-based Knowledge

pp. 137-164

Chapter 12

The Scientific Database of Medical Knowledge

pp. 165-182

Chapter 13

Debiasing Scientific Evidence for Research and Clinical Understanding

pp. 183-202

Chapter 14

Big Data and Data-intensive Medical Science

pp. 203-212

Chapter 15

Summary and Conclusions

pp. 213-214

References

pp. 215-244

Index

pp. 245-253

Series:

New Developments in Medical Research

Binding: Hardcover

Pub. Date: 2015 - 4th Quarter

Pages: 7x10 - (NBC-C)

ISBN: 978-1-63483-683-8

Status: AV

Author: Dennis Mazur

Dennis Mazur received his BA, MA, MD, and PhD from Stanford University.