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Evidence-Based Diagnosis is a textbook about diagnostic, screening, and prognostic tests in clinical medicine. The authors approach is based on many years of experience teaching physicians in a clinical research training program. Although requiring only a minimum of mathematics knowledge, the quantitative discussions in this book are deeper and more rigorous than in most introductory texts. The book includes numerous worked examples and 60 problems (with answers) based on real clinical situations and journal articles. The book will be helpful and accessible to anyone seeking to select, develop, or market medical tests. Topics covered include: the diagnostic process, test reliability and accuracy, likelihood ratios, and ROC curves, testing and treatment thresholds, critical appraisal of studies of diagnostic, screening and prognostic tests, test independence and methods of combining tests, quantifying treatment benefits using randomized trials and observational studies, Bayesian interpretation of P values and confidence intervals and challenges for evidence-based diagnosis and evidence-based medicine.
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Evidence-Based Diagnosis is a textbook about diagnostic, screening, and prognostic tests in clinical medicine. The authors approach is based on many years of experience teaching physicians in a clinical research training program. Although requiring only a minimum of mathematics knowledge, the quantitative discussions in this book are deeper and more rigorous than in most introductory texts. The book includes numerous worked examples and 60 problems (with answers) based on real clinical situations and journal articles. The book will be helpful and accessible to anyone seeking to select, develop, or market medical tests. Topics covered include: the diagnostic process, test reliability and accuracy, likelihood ratios, and ROC curves, testing and treatment thresholds, critical appraisal of studies of diagnostic, screening and prognostic tests, test independence and methods of combining tests, quantifying treatment benefits using randomized trials and observational studies, Bayesian interpretation of P values and confidence intervals and challenges for evidence-based diagnosis and evidence-based medicine.
Atsiliepimai