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A Software Tool for Exploring the Relation between Diagnostic Accuracy and Measurement Uncertainty

Hellenic Complex Systems Laboratory, Kostis Palamas 21, 66131 Drama, Greece
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Diagnostics 2020, 10(9), 610; https://doi.org/10.3390/diagnostics10090610
Received: 29 June 2020 / Revised: 26 July 2020 / Accepted: 14 August 2020 / Published: 19 August 2020
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
Screening and diagnostic tests are used to classify people with and without a disease. Diagnostic accuracy measures are used to evaluate the correctness of a classification in clinical research and practice. Although this depends on the uncertainty of measurement, there has been limited research on their relation. The objective of this work was to develop an exploratory tool for the relation between diagnostic accuracy measures and measurement uncertainty, as diagnostic accuracy is fundamental to clinical decision-making, while measurement uncertainty is critical to quality and risk management in laboratory medicine. For this reason, a freely available interactive program was developed for calculating, optimizing, plotting and comparing various diagnostic accuracy measures and the corresponding risk of diagnostic or screening tests measuring a normally distributed measurand, applied at a single point in time in non-diseased and diseased populations. This is done for differing prevalence of the disease, mean and standard deviation of the measurand, diagnostic threshold, standard measurement uncertainty of the tests and expected loss. The application of the program is illustrated with a case study of glucose measurements in diabetic and non-diabetic populations. The program is user-friendly and can be used as an educational and research tool in medical decision-making. View Full-Text
Keywords: diagnostic accuracy measures; ROC curve; measurement uncertainty; diagnostic tests; screening tests; risk diagnostic accuracy measures; ROC curve; measurement uncertainty; diagnostic tests; screening tests; risk
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MDPI and ACS Style

Chatzimichail, T.; Hatjimihail, A.T. A Software Tool for Exploring the Relation between Diagnostic Accuracy and Measurement Uncertainty. Diagnostics 2020, 10, 610. https://doi.org/10.3390/diagnostics10090610

AMA Style

Chatzimichail T, Hatjimihail AT. A Software Tool for Exploring the Relation between Diagnostic Accuracy and Measurement Uncertainty. Diagnostics. 2020; 10(9):610. https://doi.org/10.3390/diagnostics10090610

Chicago/Turabian Style

Chatzimichail, Theodora, and Aristides T. Hatjimihail 2020. "A Software Tool for Exploring the Relation between Diagnostic Accuracy and Measurement Uncertainty" Diagnostics 10, no. 9: 610. https://doi.org/10.3390/diagnostics10090610

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