Literature DB >> 14519861

Receiver operating characteristic curves and their use in radiology.

Nancy A Obuchowski1.   

Abstract

Sensitivity and specificity are the basic measures of accuracy of a diagnostic test; however, they depend on the cut point used to define "positive" and "negative" test results. As the cut point shifts, sensitivity and specificity shift. The receiver operating characteristic (ROC) curve is a plot of the sensitivity of a test versus its false-positive rate for all possible cut points. The advantages of the ROC curve as a means of defining the accuracy of a test, construction of the ROC, and identification of the optimal cut point on the ROC curve are discussed. Several summary measures of the accuracy of a test, including the commonly used percentage of correct diagnoses and area under the ROC curve, are described and compared. Two examples of ROC curve application in radiologic research are presented. Copyright RSNA, 2003

Mesh:

Year:  2003        PMID: 14519861     DOI: 10.1148/radiol.2291010898

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  183 in total

1.  Prediction of prostate cancer extracapsular extension with high spatial resolution dynamic contrast-enhanced 3-T MRI.

Authors:  B Nicolas Bloch; Elizabeth M Genega; Daniel N Costa; Ivan Pedrosa; Martin P Smith; Herbert Y Kressel; Long Ngo; Martin G Sanda; William C Dewolf; Neil M Rofsky
Journal:  Eur Radiol       Date:  2012-06-03       Impact factor: 5.315

2.  Latent classes of course in Alzheimer's disease and predictors: the Cache County Dementia Progression Study.

Authors:  Jeannie-Marie S Leoutsakos; Sarah N Forrester; Christopher D Corcoran; Maria C Norton; Peter V Rabins; Martin I Steinberg; Joann T Tschanz; Constantine G Lyketsos
Journal:  Int J Geriatr Psychiatry       Date:  2014-11-03       Impact factor: 3.485

3.  Mathematical algorithm for discovering states of expression from direct genetic comparison by microarrays.

Authors:  Hassan M Fathallah-Shaykh; Bin He; Li-Juan Zhao; Aamir Badruddin
Journal:  Nucleic Acids Res       Date:  2004-07-20       Impact factor: 16.971

4.  Mammographic system performance using an image reading qualification method.

Authors:  Silvio R Pires; Regina B Medeiros
Journal:  Radiol Phys Technol       Date:  2012-05-01

5.  Texture analysis applied to second harmonic generation image data for ovarian cancer classification.

Authors:  Bruce L Wen; Molly A Brewer; Oleg Nadiarnykh; James Hocker; Vikas Singh; Thomas R Mackie; Paul J Campagnola
Journal:  J Biomed Opt       Date:  2014-09       Impact factor: 3.170

6.  Application of a near-infrared laser tweezers Raman spectroscopy system for label-free analysis and differentiation of diabetic red blood cells.

Authors:  Jinyong Lin; Lingdong Shao; Sufang Qiu; Xingwu Huang; Mengmeng Liu; Zuci Zheng; Duo Lin; Yongliang Xu; Zhihua Li; Yao Lin; Rong Chen; Shangyuan Feng
Journal:  Biomed Opt Express       Date:  2018-02-02       Impact factor: 3.732

7.  Assessing the performance of prediction models: a framework for traditional and novel measures.

Authors:  Ewout W Steyerberg; Andrew J Vickers; Nancy R Cook; Thomas Gerds; Mithat Gonen; Nancy Obuchowski; Michael J Pencina; Michael W Kattan
Journal:  Epidemiology       Date:  2010-01       Impact factor: 4.822

Review 8.  Looking back at prospective studies.

Authors:  Carolyn M Rutter
Journal:  Acad Radiol       Date:  2008-11       Impact factor: 3.173

9.  Informatics in radiology: comparison of logistic regression and artificial neural network models in breast cancer risk estimation.

Authors:  Turgay Ayer; Jagpreet Chhatwal; Oguzhan Alagoz; Charles E Kahn; Ryan W Woods; Elizabeth S Burnside
Journal:  Radiographics       Date:  2009-11-09       Impact factor: 5.333

10.  Selection of examples in case-based computer-aided decision systems.

Authors:  Maciej A Mazurowski; Jacek M Zurada; Georgia D Tourassi
Journal:  Phys Med Biol       Date:  2008-10-14       Impact factor: 3.609

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.