Predictive Value of Tests
"Predictive Value of Tests" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.
Descriptor ID |
D011237
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MeSH Number(s) |
E05.318.780.800.650 N05.715.360.780.700.640 N06.850.520.445.800.650
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Concept/Terms |
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Below are MeSH descriptors whose meaning is more general than "Predictive Value of Tests".
Below are MeSH descriptors whose meaning is more specific than "Predictive Value of Tests".
This graph shows the total number of publications written about "Predictive Value of Tests" by people in this website by year, and whether "Predictive Value of Tests" was a major or minor topic of these publications.
To see the data from this visualization as text,
click here.
Year | Major Topic | Minor Topic | Total |
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1995 | 0 | 16 | 16 |
1996 | 0 | 5 | 5 |
1997 | 0 | 9 | 9 |
1998 | 0 | 10 | 10 |
1999 | 0 | 15 | 15 |
2000 | 0 | 18 | 18 |
2001 | 0 | 16 | 16 |
2002 | 0 | 16 | 16 |
2003 | 0 | 26 | 26 |
2004 | 0 | 43 | 43 |
2005 | 0 | 27 | 27 |
2006 | 1 | 22 | 23 |
2007 | 0 | 44 | 44 |
2008 | 0 | 29 | 29 |
2009 | 0 | 49 | 49 |
2010 | 0 | 51 | 51 |
2011 | 0 | 44 | 44 |
2012 | 0 | 34 | 34 |
2013 | 0 | 64 | 64 |
2014 | 0 | 42 | 42 |
2015 | 0 | 54 | 54 |
2016 | 0 | 52 | 52 |
2017 | 0 | 50 | 50 |
2018 | 1 | 59 | 60 |
2019 | 0 | 45 | 45 |
2020 | 1 | 50 | 51 |
2021 | 0 | 34 | 34 |
2022 | 0 | 24 | 24 |
2023 | 0 | 1 | 1 |
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Below are the most recent publications written about "Predictive Value of Tests" by people in Profiles.
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Diabetes, Atherosclerosis, and Stenosis by AI. Diabetes Care. 2023 02 01; 46(2):416-424.
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Noninvasive Evaluation of Cardiac?Chamber Pressures Using Subharmonic-Aided Pressure Estimation?With Definity Microbubbles. JACC Cardiovasc Imaging. 2023 02; 16(2):224-235.
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In the Eye of the Beholder: Defining Severe Aortic Regurgitation and the Timing of Intervention. JACC Cardiovasc Imaging. 2022 10; 15(10):1742-1744.
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Biventricular strain assessment indicates progressive impairment of myocardial contractility in phenotypically negative patients with Fabry's disease. Eur J Radiol. 2022 Oct; 155:110471.
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Discordance Between Coronary Artery Calcium Area and Density Predicts Long-Term Atherosclerotic Cardiovascular Disease Risk. JACC Cardiovasc Imaging. 2022 Nov; 15(11):1929-1940.
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Editorial for "Pediatric Cardiac Magnetic Resonance Reference Values for Biventricular Volumes Derived From Different Contouring Techniques". J Magn Reson Imaging. 2023 04; 57(4):1287-1288.
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The Prognostic Value of CAC Zero Among Individuals Presenting With Chest Pain: A Meta-Analysis. JACC Cardiovasc Imaging. 2022 10; 15(10):1745-1757.
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Evolving Role of Calcium Density in Coronary Artery Calcium Scoring and?Atherosclerotic Cardiovascular Disease Risk. JACC Cardiovasc Imaging. 2022 09; 15(9):1648-1662.
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Machine Learning for the Prevalence and Severity of Coronary Artery Calcification in Nondialysis Chronic Kidney Disease Patients: A Chinese Large Cohort Study. J Thorac Imaging. 2022 Nov 01; 37(6):401-408.
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Automated Dual-energy Computed Tomography-based Extracellular Volume Estimation for Myocardial Characterization in Patients With Ischemic and Nonischemic Cardiomyopathy. J Thorac Imaging. 2022 Sep 01; 37(5):307-314.