Literature DB >> 11484648

The assessment of quality in medical diagnostic tests: a comparison of ROC/Youden and Taguchi methods.

T Taner1, J Antony.   

Abstract

Diagnostic tests are widely used in many areas of modern technological society, but they are of particular importance in medicine, where early and accurate diagnosis can decrease morbidity and mortality rates of disease. How the quality of diagnostic information and decisions should be measured in a meaningful way has become increasingly important in recent years as an abundance of new diagnostic tests have been introduced. A number of seemingly independent indices are studied for evaluating diagnostic performance such as the receiver operating characteristic curves and signal-to-noise ratios. Designing robustness into diagnostic tests can only be achieved by minimizing the variation in the total number of false diagnosis. This article has undertaken a comparison of signal-to-noise ratios developed by Taguchi in quality engineering and system performance in manufacturing industry. A hybrid is also computed and its relevance to physicians as an efficient assessment method is proposed and strongly encouraged.

Mesh:

Year:  2000        PMID: 11484648     DOI: 10.1108/09526860010378744

Source DB:  PubMed          Journal:  Int J Health Care Qual Assur Inc Leadersh Health Serv        ISSN: 1366-0756


  4 in total

1.  An rK28-Based Immunoenzymatic Assay for the Diagnosis of Canine Visceral Leishmaniasis in Latin America.

Authors:  Marta Alicia Lauricella; Cristina Graciela Maidana; Victoria Fragueiro Frias; Carlo M Romagosa; Vanesa Negri; Ruben Benedetti; Angel J Sinagra; Concepcion Luna; Lilian Tartaglino; Susana Laucella; Steven G Reed; Adelina R Riarte
Journal:  Am J Trop Med Hyg       Date:  2016-05-09       Impact factor: 2.345

2.  Machine Learning Approaches for Predicting Difficult Airway and First-Pass Success in the Emergency Department: Multicenter Prospective Observational Study.

Authors:  Syunsuke Yamanaka; Tadahiro Goto; Koji Morikawa; Hiroko Watase; Hiroshi Okamoto; Yusuke Hagiwara; Kohei Hasegawa
Journal:  Interact J Med Res       Date:  2022-01-25

3.  Machine-Learning Approaches for Predicting the Need of Oxygen Therapy in Early-Stage COVID-19 in Japan: Multicenter Retrospective Observational Study.

Authors:  Syunsuke Yamanaka; Koji Morikawa; Hiroyuki Azuma; Maki Yamanaka; Yoshimitsu Shimada; Toru Wada; Hideyuki Matano; Naoki Yamada; Osamu Yamamura; Hiroyuki Hayashi
Journal:  Front Med (Lausanne)       Date:  2022-02-23

4.  Evaluation of the Taguchi methods for the simultaneous assessment of the effects of multiple variables in the tumour microenvironment.

Authors:  Hisham Morsi; Kwee L Yong; Andrew P Jewell
Journal:  Int Semin Surg Oncol       Date:  2004-09-20
  4 in total

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