Results 91 to 100 of about 3,642,241 (237)

An Improved Method for Bandwidth Selection when Estimating ROC Curves [PDF]

The receiver operating characteristic (ROC) curve is used to describe the performance of a diagnostic test which classifies observations into two groups.
Peter Hall, Rob J. Hyndman
core  

Receiver Operating Characteristic Curve of FOMmiR predictor.

, 2013
Receiver Operating Characteristic Curve of FOMmiR predictor.
Guo Wei (79839), Yan Li (23143), Ming Chen (115604), Wei Shen (149127)   +3 more
core   +1 more source

Hierarchical Summary Receiver Operating Characteristic Curve.

, 2015
Hierarchical Summary Receiver Operating Characteristic Curve.
Shunichi Fukuhara (316094), Shin Yamazaki (225918), Toshihiko Takada (743704), Shingo Fukuma (685099), Yoshinori Noguchi (14737), Hiroki Nishiwaki (791239), Yosuke Yamamoto (791240)   +6 more
core   +1 more source

Contingency table for calculating the receiver operating characteristic curve.

, 2022
Contingency table for calculating the receiver operating characteristic curve.
Lijun Cheng (3469445), Lang Li (91927), Birkan Gokbag (12400986), Pratik Karkhanis (12400983), Yueze Liu (12400989)   +4 more
core   +1 more source

Receiver-operating characteristic curve for SPTB-PPROM.

, 2012
Receiver-operating characteristic curve for SPTB-PPROM.
Claire T. Roberts (103366), Gustaaf Albert Dekker (150939), Lesley M. McCowan (150948), Nigel A. B. Simpson (150950), Robyn A. North (150945), Shalem Y. Lee (150942)   +5 more
core   +1 more source

Receiver operating characteristic curve for FIB-4 and mortality.

, 2021
Receiver operating characteristic curve for FIB-4 and mortality.
Sri Agustini Kurniawati (11472884), Anisa Hana Syafiyah (11472890), Achmad Mulawarman Jayusman (11472887), Raymond Pranata (8896589), Noorwati Sutandyo (11472881), Arif Riswahyudi Hanafi (11472893)   +5 more
core   +1 more source

The use of receiver operating characteristic curves in biomedical informatics

Journal of Biomedical Informatics, 2005
Receiver operating characteristic (ROC) curves are frequently used in biomedical informatics research to evaluate classification and prediction models for decision support, diagnosis, and prognosis. ROC analysis investigates the accuracy of a model's ability to separate positive from negative cases (such as predicting the presence or absence of disease)
Thomas A. Lasko, Jui G. Bhagwat, Kelly H. Zou, Lucila Ohno-Machado   +3 more
openaire   +2 more sources

Association between body mass index and diabetes mellitus in tuberculosis patients in China: a community based cross-sectional study

BMC Public Health, 2017
Background We planned to determine the association of body mass index (BMI) with diabetes mellitus (DM) and impaired fasting glucose (IFG) in Chinese pulmonary tuberculosis (PTB) patients.
Jing Cai, Aiguo Ma, Qiuzhen Wang, Xiuxia Han, Shanliang Zhao, Yu Wang, Evert G. Schouten, Frans J. Kok   +7 more
doaj   +1 more source

Receiver Operating Characteristic Curve in Diagnostic Test Assessment [PDF]

Journal of Thoracic Oncology, 2010
The performance of a diagnostic test in the case of a binary predictor can be evaluated using the measures of sensitivity and specificity. However, in many instances, we encounter predictors that are measured on a continuous or ordinal scale. In such cases, it is desirable to assess performance of a diagnostic test over the range of possible cutpoints ...
openaire   +2 more sources

Parameters behind "nonparametric" statistics: Kendall's tau,Somers' D and median differences [PDF]

So-called "nonparametric" statistical methods are often in fact based on population parameters, which can be estimated (with confidence limits) using the corresponding sample statistics.
Roger Newson
core