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Evidence-Based Diagnosis: An Introduction to Clinical Epidemiology 2nd Revised edition [Mīkstie vāki]

(University of California, San Francisco), (University of California, San Francisco)
  • Formāts: Paperback / softback, 405 pages, height x width x depth: 235x156x16 mm, weight: 650 g, Worked examples or Exercises
  • Izdošanas datums: 25-Jun-2020
  • Izdevniecība: Cambridge University Press
  • ISBN-10: 1108436714
  • ISBN-13: 9781108436717
Citas grāmatas par šo tēmu:
  • Mīkstie vāki
  • Cena: 59,92 €
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  • Formāts: Paperback / softback, 405 pages, height x width x depth: 235x156x16 mm, weight: 650 g, Worked examples or Exercises
  • Izdošanas datums: 25-Jun-2020
  • Izdevniecība: Cambridge University Press
  • ISBN-10: 1108436714
  • ISBN-13: 9781108436717
Citas grāmatas par šo tēmu:
Medicine is becoming increasingly reliant on diagnostic, prognostic and screening tests for the successful treatment of patients. With new tests being developed all the time, a more informed understanding of the benefits and drawbacks of these tests is crucial. Providing readers with the tools needed to evaluate and interpret these tests, numerous real-world examples demonstrate the practical application and relevance of the material. The mathematics involved are rigorously explained using simple and informative language. Topics covered include the diagnostic process, reliability and accuracy of tests, and quantifying treatment benefits using randomized trials, amongst others. Engaging illustrations act as visual representations of the concepts discussed in the book, complementing the textual explanation. Based on decades of experience teaching in a clinical research training program, this fully updated second edition is an essential guide for anyone looking to select, develop or market medical tests.

A rigorous yet engaging guide to understanding and choosing a range of diagnostic and prognostic tests. Topics explored include the diagnostic process, the reliability and accuracy of different tests and quantifying treatment benefits using randomized trails. Numerous worked examples and problems based on real situations support readers' learning.

Papildus informācija

Explains the mathematics involved in understanding and choosing an array of diagnostic and prognostic tests, in order to improve treatment.
Preface ix
Acknowledgments x
1 Introduction: Understanding Diagnosis and Evidence-Based Diagnosis
1(7)
2 Dichotomous Tests
8(39)
3 Multilevel and Continuous Tests
47(28)
4 Critical Appraisal of Studies of Diagnostic Test Accuracy
75(35)
5 Reliability and Measurement Error
110(34)
6 Risk Predictions
144(31)
7 Multiple Tests and Multivariable Risk Models
175(30)
8 Quantifying Treatment Effects Using Randomized Trials
205(26)
9 Alternatives to Randomized Trials for Estimating Treatment Effects
231(19)
10 Screening Tests
250(30)
11 Understanding P-Values and Confidence Intervals
280(23)
12 Challenges for Evidence-Based Diagnosis
303(15)
Answers to Problems 318(39)
Index 357
Thomas B. Newman is the Professor Emeritus of Epidemiology & Biostatistics and Pediatrics at the University of California San Francisco, USA. Michael A. Kohn is a Professor of Epidemiology & Biostatistics at the University of California San Francisco, USA.