Reproducibility In Biomedical Research
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Reproducibility in Biomedical Research
Reproducibility in Biomedical Research: Epistemological and Statistical Problems, 2nd Ed. explores the ideas and conundrums inherent in scientific research. Reproducibility is one of the biggest challenges in biomedical research. It affects not only the ability to replicate results, but the very trust in the findings. Since published in 2019, Reproducibility of Biomedical Research: Epistemological and Statistical Problems established itself as a solid ethical reference in the area, leading to significant reflection on biomedical research. The second edition addresses new challenges to reproducibility in biosciences, namely reproducibility of machine learning Artificial Intelligence (AI), reproducibility of translation from research to medical care, and the fundamental challenges to reproducibility. All current chapters will be expanded to cover advances in the topics previously addressed. Reproducibility in Biomedical Research: Epistemological and Statistical Problems, 2nd Ed. provides biomedical researchers with a framework to better understand the reproducibility challenges in the area. Newly introduced interactive exercises and updated case studies help students understand the fundamental concepts involved in the area. - Includes four new chapters and updates across the book, covering recent developments of issues affecting reproducibility in biomedical research - Covers reproducibility of results from machine learning AI algorithms - Presents new case studies to illustrate challenges in related fields - Includes a companion website with interactive exercises and summary tables
Enhancing Scientific Reproducibility in Biomedical Research Through Transparent Reporting
Author: National Academies of Sciences, Engineering, and Medicine
language: en
Publisher: National Academies Press
Release Date: 2020-05-28
Sharing knowledge is what drives scientific progress - each new advance or innovation in biomedical research builds on previous observations. However, for experimental findings to be broadly accepted as credible by the scientific community, they must be verified by other researchers. An essential step is for researchers to report their findings in a manner that is understandable to others in the scientific community and provide sufficient information for others to validate the original results and build on them. In recent years, concern has been growing over a number of studies that have failed to replicate previous results and evidence from larger meta-analyses, which have pointed to the lack of reproducibility in biomedical research. On September 25 and 26, 2019, the National Academies of Science, Engineering, and Medicine hosted a public workshop in Washington, DC, to discuss the current state of transparency in the reporting of preclinical biomedical research and to explore opportunities for harmonizing reporting guidelines across journals and funding agencies. Convened jointly by the Forum on Drug Discovery, Development, and Translation; the Forum on Neuroscience and Nervous System Disorders; the National Cancer Policy Forum; and the Roundtable on Genomics and Precision Health, the workshop primarily focused on transparent reporting in preclinical research, but also considered lessons learned and best practices from clinical research reporting. This publication summarizes the presentation and discussion of the workshop.
Reproducibility in Biomedical Research
Author: Erwin B. Montgomery Jr.
language: en
Publisher: Academic Press
Release Date: 2019-03-14
Reproducibility in Biomedical Research: Epistemological and Statistical Problems explores the ideas and conundrums inherent in scientific research. It explores factors of reproducibility, including logic, distinguishing productive from unproductive irreproducibility, the scientific method, and the use of statistics. In multiple examples and six detailed case studies, the book demonstrates the misuse of logic resulting in unproductive irreproducibility, allowing researchers to develop their own logic and planning abilities. Biomedical researchers, clinicians, administrators of scientific institutions and funding agencies, journal editors, philosophers of science and medicine will find the arguments and explorations a valuable addition to their libraries. - Considers the meaning and purpose of reproducibility to help design research - Reviews famous case studies of alleged irreproducibility to determine if these could be reproducible - Provides a theoretical aspect to practical issues surrounding research design and conduct