Ask
Search
My library

About
Statistics
Contact
Data Protection
Accessibility
Imprint
Changelog
Frontend: v1.31.3
Backend: v1.11.4

We use cookies to provide a better user experience.

Data Protection

ROC analyses for clinical risk score, or the combination of p53 or p53 plus JWA.

Xin Liu (43569)
Shouyu Wang (109860)
Xiaowei Xia (109862)
Yansu Chen (109864)
Yan Zhou (6523)
Xuming Wu (109866)
Jianbing Zhang (109867)
Song He (102931)
Yongfei Tan (109868)
Fulin Qiang (109869)
Oluf Dimitri Røe (109870)
Gang Li (34549)
Jianwei Zhou (109871)

Publication date

December 2012

DOI

10.1371/journal.pone.0052348.g003

Abstract

<p>(A) Time-dependent ROC analyses in the training cohort. (B) Time-dependent ROC analyses in the testing cohort. AUC = area under the curve.</p

Extracted data

Topics

Related items

ROC curves for predicting adverse event.

Susana Gordo-Remartínez (748107)
María Calderón-Moreno (748108)
Juan Fernández-Herranz (748109)
Ana Castuera-Gil (748110)
Mar Gallego-Alonso-Colmenares (748111)
Carolina Puertas-López (748112)
José A. Nuevo-González (748113)
Domingo Sánchez-Sendín (748114)
Mercedes García-Gámiz (748115)
José A. Sevillano-Fernández (748116)
Luis A. Álvarez-Sala (748117)
Juan A. Andueza-Lillo (748118)
José M. de Miguel-Yanes (748119)

June 2015

<p>Fig 3a. ROC curves for different biomarkers and PSI. Fig 3b. ROC curves for the PSI & MR-proADM p...

ROC curve results.

Hyuk Jin Yun (281662)
Kiho Im (105337)
Jin-Ju Yang (281663)
Uicheul Yoon (281664)
Jong-Min Lee (105338)

February 2013

<p>ROC curves are plots of sensitivity and specificity of algorithms for distinguishing normal contr...

ROC curve analysis for anthropometric measures a metabolic syndrome (ATP III criteria).

Miquel Bennasar-Veny (416460)
Angel A. Lopez-Gonzalez (416461)
Pedro Tauler (327102)
Mey L. Cespedes (327098)
Teofila Vicente-Herrero (416462)
Aina Yañez (416463)
Matias Tomas-Salva (416464)
Antoni Aguilo (327104)

May 2013

<p>ROC curve analysis for anthropometric measures a metabolic syndrome (ATP III criteria).</p

The ROC curves for the biomarkers and the severity scores.

Yanyan Zhou (158996)
Haiyun Dong (794468)
Yanjun Zhong (794469)
Jia Huang (42138)
Jianlei Lv (794470)
Jinxiu Li (221935)

September 2015

<p>The areas under the ROC curve (AUCs) for the CIRP level, the APACHE II score, the SOFA score, the...

ROC curves comparing measured PSA to genetically corrected PSA risk score using the 4 PSA-SNPs.

Rebecca Gilbert (803090)
Richard M. Martin (176602)
David M. Evans (152874)
Kate Tilling (213507)
George Davey Smith (82619)
John P. Kemp (152856)
J. Athene Lane (360647)
Freddie C. Hamdy (184070)
David E. Neal (6580)
Jenny L. Donovan (194899)
Chris Metcalfe (528710)

October 2015

<p>Area under the curve (AUC) comparing measured PSA, genetically corrected PSA risk score based on ...

ROC curve (receiver operating characteristic curve) and area under curves (AUCs) of the validation cohort by different cancer stages.

Yung-Heng Lee (6204656)
Pei-Tseng Kung (593657)
Yueh-Hsin Wang (593658)
Wei-Yin Kuo (5439602)
Su-Ling Kao (6204659)
Wen-Chen Tsai (593659)

January 2019

ROC curve (receiver operating characteristic curve) and area under curves (AUCs) of the validation c...

ROC analysis for the immunohistochemistry cut-off score.

Zongtai Li (484474)
Xiaofang Zou (484475)
Liangxi Xie (409841)
Hongmei Dong (409840)
Yuping Chen (484476)
Qing Liu (20889)
Xiao Wu (158273)
David Zhou (484477)
Dongfeng Tan (59024)
Hao Zhang (15339)

November 2013

<p>The sensitivity and specificity for each clinical outcome were plotted (A–F). Accuracy was measur...

ROC curve for a) endoscopically visible CLE of any length independent of histology (AUC: 0.61), b) segment containing IM≥2 cm (AUC: 0.64) in the external validation cohort (N = 477).

Xinxue Liu (322346)
Angela Wong (552360)
Sudarshan R. Kadri (552361)
Andrej Corovic (552362)
Maria O’Donovan (552363)
Pierre Lao-Sirieix (23325)
Laurence B. Lovat (552364)
Rodney W. Burnham (552365)
Rebecca C. Fitzgerald (23326)

April 2014

<p>ROCs curve were developed using the risk scores which are calculated by the weights of different ...

AUC (95% C.I.) of the ROC curve analysis to discriminate patients and controls, patients with DR and participants without DR, and patients with CSME and participants without CSME.

Li-Ting Tsai (3111165)
Kuo-Meng Liao (3111162)
Yuh Jang (3111159)
Fu-Chang Hu (177537)
Wei-Chi Wu (287560)

September 2016

<p>AUC (95% C.I.) of the ROC curve analysis to discriminate patients and controls, patients with DR ...

ROC curve for a) endoscopically visible CLE of any length independent of histology (AUC: 0.72), b) segment containing IM≥2 cm (AUC: 0.81) in the training cohort (N = 1603).

Xinxue Liu (322346)
Angela Wong (552360)
Sudarshan R. Kadri (552361)
Andrej Corovic (552362)
Maria O’Donovan (552363)
Pierre Lao-Sirieix (23325)
Laurence B. Lovat (552364)
Rodney W. Burnham (552365)
Rebecca C. Fitzgerald (23326)

April 2014

<p>ROCs curve were developed using the risk scores which are calculated using the weights of differe...

ROC curves for the mortality model, using test data (AUC values are indicated on the graph).

Raïsa Carmen (6490166)
Galit B. Yom-Tov (6490169)
Inneke Van Nieuwenhuyse (6490172)
Bram Foubert (6490175)
Yishai Ofran (306566)

March 2019

ROC curves for the mortality model, using test data (AUC values are indicated on the graph).</p

Estimated ROC curve analysis using the three parameters to predict primary origin.

Cheol Keun Park (466851)
Douglas P. Malinowski (5537129)
Nam Hoon Cho (2047729)

July 2018

<p>(A) In stomach cancer, AUC was 0.8699. (B) In ovarian cancer, the AUC was 0.9812. (C) In lung can...

ROC curves comparing marker concentrations in cases to healthy controls for sample set 1.

Jing Wu (54032)
Haidi Yin (709697)
Jianhui Zhu (678784)
Ronald J. Buckanovich (324163)
Jason D. Thorpe (257341)
Jianliang Dai (29566)
Nicole Urban (95152)
David M. Lubman (591282)

March 2015

<p>(a) ROC analyses for CA125 and LRG1 to differentiate EOC from healthy controls. (b) ROC analyses ...

ROC curve analysis.

Xin Luo (428648)
Jijia Sun (13202211)
Hong Pan (8686)
Dian Zhou (5958284)
Ping Huang (30439)
Jingjing Tang (419372)
Rong Shi (23893)
Hong Ye (460576)
Ying Zhao (16546)
An Zhang (409592)

August 2023

(A) Performance of the model in the training set, which showed an AUC value of 0.768, an optimal cut...

ROC curve analysis.

Bernhard Hametner (819993)
Stephanie Parragh (819994)
Thomas Weber (819995)
Siegfried Wassertheurer (819998)

June 2017

<p>Left: Comparison of the ROC curves obtained with central pulse pressure (PP), ejection duration (...

ROC curves for predicting adverse event.

Susana Gordo-Remartínez (748107)
María Calderón-Moreno (748108)
Juan Fernández-Herranz (748109)
Ana Castuera-Gil (748110)
Mar Gallego-Alonso-Colmenares (748111)
Carolina Puertas-López (748112)
José A. Nuevo-González (748113)
Domingo Sánchez-Sendín (748114)
Mercedes García-Gámiz (748115)
José A. Sevillano-Fernández (748116)
Luis A. Álvarez-Sala (748117)
Juan A. Andueza-Lillo (748118)
José M. de Miguel-Yanes (748119)

June 2015

<p>Fig 3a. ROC curves for different biomarkers and PSI. Fig 3b. ROC curves for the PSI & MR-proADM p...

ROC curve results.

Hyuk Jin Yun (281662)
Kiho Im (105337)
Jin-Ju Yang (281663)
Uicheul Yoon (281664)
Jong-Min Lee (105338)

February 2013

<p>ROC curves are plots of sensitivity and specificity of algorithms for distinguishing normal contr...

ROC curve analysis for anthropometric measures a metabolic syndrome (ATP III criteria).

Miquel Bennasar-Veny (416460)
Angel A. Lopez-Gonzalez (416461)
Pedro Tauler (327102)
Mey L. Cespedes (327098)
Teofila Vicente-Herrero (416462)
Aina Yañez (416463)
Matias Tomas-Salva (416464)
Antoni Aguilo (327104)

May 2013

<p>ROC curve analysis for anthropometric measures a metabolic syndrome (ATP III criteria).</p

The ROC curves for the biomarkers and the severity scores.

Yanyan Zhou (158996)
Haiyun Dong (794468)
Yanjun Zhong (794469)
Jia Huang (42138)
Jianlei Lv (794470)
Jinxiu Li (221935)

September 2015

<p>The areas under the ROC curve (AUCs) for the CIRP level, the APACHE II score, the SOFA score, the...

ROC curves comparing measured PSA to genetically corrected PSA risk score using the 4 PSA-SNPs.

Rebecca Gilbert (803090)
Richard M. Martin (176602)
David M. Evans (152874)
Kate Tilling (213507)
George Davey Smith (82619)
John P. Kemp (152856)
J. Athene Lane (360647)
Freddie C. Hamdy (184070)
David E. Neal (6580)
Jenny L. Donovan (194899)
Chris Metcalfe (528710)

October 2015

<p>Area under the curve (AUC) comparing measured PSA, genetically corrected PSA risk score based on ...

ROC curve (receiver operating characteristic curve) and area under curves (AUCs) of the validation cohort by different cancer stages.

Yung-Heng Lee (6204656)
Pei-Tseng Kung (593657)
Yueh-Hsin Wang (593658)
Wei-Yin Kuo (5439602)
Su-Ling Kao (6204659)
Wen-Chen Tsai (593659)

January 2019

ROC curve (receiver operating characteristic curve) and area under curves (AUCs) of the validation c...

ROC analysis for the immunohistochemistry cut-off score.

Zongtai Li (484474)
Xiaofang Zou (484475)
Liangxi Xie (409841)
Hongmei Dong (409840)
Yuping Chen (484476)
Qing Liu (20889)
Xiao Wu (158273)
David Zhou (484477)
Dongfeng Tan (59024)
Hao Zhang (15339)

November 2013

<p>The sensitivity and specificity for each clinical outcome were plotted (A–F). Accuracy was measur...

ROC curve for a) endoscopically visible CLE of any length independent of histology (AUC: 0.61), b) segment containing IM≥2 cm (AUC: 0.64) in the external validation cohort (N = 477).

Xinxue Liu (322346)
Angela Wong (552360)
Sudarshan R. Kadri (552361)
Andrej Corovic (552362)
Maria O’Donovan (552363)
Pierre Lao-Sirieix (23325)
Laurence B. Lovat (552364)
Rodney W. Burnham (552365)
Rebecca C. Fitzgerald (23326)

April 2014

<p>ROCs curve were developed using the risk scores which are calculated by the weights of different ...

AUC (95% C.I.) of the ROC curve analysis to discriminate patients and controls, patients with DR and participants without DR, and patients with CSME and participants without CSME.

Li-Ting Tsai (3111165)
Kuo-Meng Liao (3111162)
Yuh Jang (3111159)
Fu-Chang Hu (177537)
Wei-Chi Wu (287560)

September 2016

<p>AUC (95% C.I.) of the ROC curve analysis to discriminate patients and controls, patients with DR ...

ROC curve for a) endoscopically visible CLE of any length independent of histology (AUC: 0.72), b) segment containing IM≥2 cm (AUC: 0.81) in the training cohort (N = 1603).

Xinxue Liu (322346)
Angela Wong (552360)
Sudarshan R. Kadri (552361)
Andrej Corovic (552362)
Maria O’Donovan (552363)
Pierre Lao-Sirieix (23325)
Laurence B. Lovat (552364)
Rodney W. Burnham (552365)
Rebecca C. Fitzgerald (23326)

April 2014

<p>ROCs curve were developed using the risk scores which are calculated using the weights of differe...

ROC curves for the mortality model, using test data (AUC values are indicated on the graph).

Raïsa Carmen (6490166)
Galit B. Yom-Tov (6490169)
Inneke Van Nieuwenhuyse (6490172)
Bram Foubert (6490175)
Yishai Ofran (306566)

March 2019

ROC curves for the mortality model, using test data (AUC values are indicated on the graph).</p

Estimated ROC curve analysis using the three parameters to predict primary origin.

Cheol Keun Park (466851)
Douglas P. Malinowski (5537129)
Nam Hoon Cho (2047729)

July 2018

<p>(A) In stomach cancer, AUC was 0.8699. (B) In ovarian cancer, the AUC was 0.9812. (C) In lung can...

ROC curves comparing marker concentrations in cases to healthy controls for sample set 1.

Jing Wu (54032)
Haidi Yin (709697)
Jianhui Zhu (678784)
Ronald J. Buckanovich (324163)
Jason D. Thorpe (257341)
Jianliang Dai (29566)
Nicole Urban (95152)
David M. Lubman (591282)

March 2015

<p>(a) ROC analyses for CA125 and LRG1 to differentiate EOC from healthy controls. (b) ROC analyses ...

ROC curve analysis.

Xin Luo (428648)
Jijia Sun (13202211)
Hong Pan (8686)
Dian Zhou (5958284)
Ping Huang (30439)
Jingjing Tang (419372)
Rong Shi (23893)
Hong Ye (460576)
Ying Zhao (16546)
An Zhang (409592)

August 2023

(A) Performance of the model in the training set, which showed an AUC value of 0.768, an optimal cut...

ROC curve analysis.

Bernhard Hametner (819993)
Stephanie Parragh (819994)
Thomas Weber (819995)
Siegfried Wassertheurer (819998)

June 2017

<p>Left: Comparison of the ROC curves obtained with central pulse pressure (PP), ejection duration (...

ROC curves for predicting adverse event.

Susana Gordo-Remartínez (748107)
María Calderón-Moreno (748108)
Juan Fernández-Herranz (748109)
Ana Castuera-Gil (748110)
Mar Gallego-Alonso-Colmenares (748111)
Carolina Puertas-López (748112)
José A. Nuevo-González (748113)
Domingo Sánchez-Sendín (748114)
Mercedes García-Gámiz (748115)
José A. Sevillano-Fernández (748116)
Luis A. Álvarez-Sala (748117)
Juan A. Andueza-Lillo (748118)
José M. de Miguel-Yanes (748119)

June 2015

<p>Fig 3a. ROC curves for different biomarkers and PSI. Fig 3b. ROC curves for the PSI & MR-proADM p...

ROC curve results.

Hyuk Jin Yun (281662)
Kiho Im (105337)
Jin-Ju Yang (281663)
Uicheul Yoon (281664)
Jong-Min Lee (105338)

February 2013

<p>ROC curves are plots of sensitivity and specificity of algorithms for distinguishing normal contr...

ROC curve analysis for anthropometric measures a metabolic syndrome (ATP III criteria).

Miquel Bennasar-Veny (416460)
Angel A. Lopez-Gonzalez (416461)
Pedro Tauler (327102)
Mey L. Cespedes (327098)
Teofila Vicente-Herrero (416462)
Aina Yañez (416463)
Matias Tomas-Salva (416464)
Antoni Aguilo (327104)

May 2013

<p>ROC curve analysis for anthropometric measures a metabolic syndrome (ATP III criteria).</p