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£111.73
Springer Diagnostic Meta-Analysis: A Useful Tool for Clinical Decision-Making
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Price distribution over 75 days • 2 price levels
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Most common price: £113 (55 days, 73.3%)
Price range: £112 - £113
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Description
Product Description This book is the first exclusively devoted to the systematic synthesis of diagnostic test accuracy studies. It builds upon the major recent developments in reporting standards, search methods, and, in particular, statistical tools specifically devoted to diagnostic studies. In addition, it borrows extensively from the latest advances in systematic reviews and meta-analyses of intervention studies. After a section dedicated to methods for designing reviews, synthesizing evidence and appraising inconsistency in research, the application of these approaches is demonstrated in the context of case studies from various clinical disciplines. Diagnosis is central in medical decision-making, and in many other fields of human endeavor, such as education and psychology. The plurality of sources of evidence on diagnostic test accuracy poses a huge challenge for practitioners and researchers, as do the multiple dimensions of evidence validity, which include sensitivity, specificity, predictive values, and likelihood ratios. This book offers an invaluable resource for anyone aiming to improve decision-making processes in diagnosis, classification or risk prognostication, from epidemiologists to biostatisticians, radiologists, laboratory physicians and graduate students, as any physician interested in refining his methodological skills in clinical diagnosis. Review “In this book, the authors present pragmatic and useful summaries of the necessary steps for conducting diagnostic accuracy meta-analysis. … This is a great addition to this field, which has lacked a comprehensive introductory book intended for beginners. While the Cochrane handbook also provides a good summary of this topic, this book reaches a broader audience.” (Michihiko Goto, Doody's Book Reviews, April 12, 2019) From the Back Cover This book is the first exclusively devoted to the systematic synthesis of diagnostic test accuracy studies. It builds upon the major recent developments in reporting standards, search methods, and, in particular, statistical tools specifically devoted to diagnostic studies. In addition, it borrows extensively from the latest advances in systematic reviews and meta-analyses of intervention studies. After a section dedicated to methods for designing reviews, synthesizing evidence and appraising inconsistency in research, the application of these approaches is demonstrated in the context of case studies from various clinical disciplines. Diagnosis is central in medical decision-making, and in many other fields of human endeavor, such as education and psychology. The plurality of sources of evidence on diagnostic test accuracy poses a huge challenge for practitioners and researchers, as do the multiple dimensions of evidence validity, which include sensitivity, specificity, predictive values, and likelihood ratios. This book offers an invaluable resource for anyone aiming to improve decision-making processes in diagnosis, classification or risk prognostication, from epidemiologists to biostatisticians, radiologists, laboratory physicians and graduate students, as any physician interested in refining his methodological skills in clinical diagnosis. About the Author Giuseppe Biondi-Zoccai is Associate Professor in Cardiology in the Department of Medico-Surgical Sciences and Biotechnologies of Sapienza University of Rome. He has got an established expertise in evidence-based cardiovascular medicine and is the founder of the Meta-analysis and Evidence-based medicine Training in Cardiology (METCARDIO) Collaboration. He has published more than 600 articles indexed in MEDLINE, including more than 200 systematic reviews, meta-analyses, or umbrella reviews, and he is the editor of the first books devoted to network meta-analyses and umbrella reviews.
Product Specifications
- Brand
- Springer
- Format
- hardcover
- ASIN
- 3319789651
- Domain
- Amazon UK
- Release Date
- 16 August 2018
- Listed Since
- 08 March 2018
Barcode
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