Survival curves according to the optimal cut-off value derived by ROC analysis for preoperative pulmonary vascular resistance (PVR).

ROC curve for linear regression model calculated with the parameters age, average platelet count on day 10, average pump flow rate on day 10, minimum partial pressure of oxygen on day 10, and average pH on day 10 after the start of veno-venous extracorporeal membrane oxygenation.

Bärbel Kieninger (11502108)
Magdalena Kilger (3450395)
Maik Foltan (668125)
Michael Gruber (318913)
Dirk Lunz (668127)
Thomas Dienemann (3415745)
Stephan Schmid (3608621)
Bernhard Graf (522352)
Clemens Wiest (13165305)
Matthias Lubnow (668123)
Thomas Müller (3554)
Bernd Salzberger (801373)
Wulf Schneider-Brachert (320442)
Martin Kieninger (11502096)

January 2023

The yellow arrow is at a separation value of 0.85 with a sensitivity of 61.9 and a specificity of 97...

Volume status for predicting mortality.

Szu-Chun Hung (114864)
Yao-Ping Lin (114868)
Hsin-Lei Huang (383499)
Hsiao-Fung Pu (383500)
Der-Cherng Tarng (114877)

March 2013

The receiver operating characteristic (ROC) curve for prediction of all-cause mortality construct...

ROC curve for determining the cut-off value of serum CMV viral load for the development of (i) CMV end organ diseases (EODs) (left) and (ii) Disseminated CMV EODs (right).

Avirup Chakraborty (2218096)
Tanmay Mahapatra (484660)
Sanchita Mahapatra (509306)
Sabbir Ansari (2218090)
Sattik Siddhanta (2218099)
Siwalik Banerjee (2218102)
Dipanjan Banerjee (1445326)
Rathindra Nath Sarkar (2218093)
Subhashish Kamal Guha (2218087)
Nilanjan Chakraborty (604285)

February 2015

ROC curve for determining the cut-off value of serum CMV viral load for the development of (i) CM...

The optimal cut-off levels of 91H relative expression were determined based on the largest of sensitivity and specificity by receiver operating characteristic curve (ROC) analysis for overall survival.

Qiwen Deng (530955)
Bangshun He (119526)
Tianyi Gao (119544)
Yuqin Pan (119528)
Huiling Sun (530956)
Yeqiong Xu (119533)
Rui Li (4631)
Houqun Ying (603739)
Feng Wang (44414)
Xian Liu (191882)
Jie Chen (5892)
Shukui Wang (119550)

July 2014

The optimal cut-off levels of 91H relative expression were determined based on the largest of sen...

ROC curves for the determination of the overall performance of the assay and the optimal cut-off value for each mutant's index.

Velizar Shivarov (464941)
Milena Ivanova (464942)
Elissaveta Naumova (95112)

June 2014

ROC curves for the determination of the overall performance of the assay and the optimal cut-off ...

Receiver operating characteristic (ROC) curve defining cutoff levels predicting outcomes in eligible trials with molecularly selected patients in terms of the progression-free survival-hazard ratio (PFS-HR) (A) and the odds ratio for the overall response (B).

Katsuyuki Hotta (78500)
Yuka Kato (9286)
Natasha Leighl (703141)
Nagio Takigawa (144711)
Rabab Mohamed Gaafar (703142)
Hiroe Kayatani (703143)
Taizo Hirata (309169)
Kadoaki Ohashi (703144)
Toshio Kubo (703145)
Masahiro Tabata (144716)
Mitsune Tanimoto (78508)
Katsuyuki Kiura (78507)

March 2015

The most suitable cutoff was defined as that closest to the upper left corner. A, A PFS-HR of 0.6...

Receiver Operating Characteristic (ROC) curve for the best cut-off point of Glasgow Coma Scale (GCS) that predicts survival.

Mohamed A. Al-Ali (14192745)
David O. Alao (11442104)
Fikri M. Abu-Zidan (8638308)

November 2022

Receiver Operating Characteristic (ROC) curve for the best cut-off point of Glasgow Coma Scale (GCS)...

Optimal cut-off, area under the ROC-curve (Area), and diagnostic sensitivity and specificity of statistically significant biochemical markers.

Marie Åsberg (374799)
Åke Nygren (374800)
Rosario Leopardi (374801)
Gunnar Rylander (374802)
Ulla Peterson (374803)
Lukas Wilczek (374804)
Håkan Källmén (374806)
Mirjam Ekstedt (374808)
Torbjörn Åkerstedt (3343088)
Mats Lekander (226776)
Rolf Ekman (369536)

February 2013

Optimal cut-off, area under the ROC-curve (Area), and diagnostic sensitivity and specificity of s...

Prognostic ROC curves: a method for representing the overall discriminative capacity of binary markers with right-censored time-to-event endpoints

Combescure, Christophe
Perneger, Thomas
Weber, Damien
Daurès, Jean-Pierre
Foucher, Yohann

January 2014

Survival curves are a popular tool for representing the association between a binary marker and the ...

ROC curve showing optimal cut-off value of 3 mm (sensitivity, 0.795; specificity, 0.61).

Hajime Ushigome (6321017)
Yosuke Fukunaga (4056700)
Toshiya Nagasaki (3438119)
Takashi Akiyoshi (4056697)
Tsuyoshi Konishi (4056691)
Yoshiya Fujimoto (4056703)
Satoshi Nagayama (105355)
Masashi Ueno (4056694)

February 2019

ROC curve showing optimal cut-off value of 3 mm (sensitivity, 0.795; specificity, 0.61).</p

Defining an Optimal Cut-Point Value in ROC Analysis: An Alternative Approach

Ünal, İlker

ROC curve analysis is often applied to measure the diagnostic accuracy of a biomarker. The analysis ...

Kaplan Meier curves showing the cumulative survival for those with and without PAE and for pulmonary artery diameter quartiles.

Juan P. de-Torres (400034)
Ana Ezponda (4951021)
Ana B. Alcaide (400035)
Arantza Campo (400039)
Juan Berto (2621371)
Jessica Gonzalez (3621353)
Javier J. Zulueta (400042)
Ciro Casanova (357425)
Luisa Elena Rodriguez-Delgado (5142602)
Bartolome R. Celli (204834)
Gorka Bastarrika (400037)

April 2018

Kaplan Meier curves showing the cumulative survival for those with and without PAE and for pulmon...

ROC curves of the RCSI score and CTSI score in predicting the mortality.

Haotong Xu (197706)
Lukas Ebner (403773)
Shiming Jiang (629653)
Yi Wu (197719)
Andreas Christe (403772)
Shaoxiang Zhang (197722)
Xiaoming Zhang (104062)
Zhulin Luo (403774)
Fuzhou Tian (403775)

September 2014

(a: cutoff value = 4.0, sensitivity = 82.11%, specificity = 96.91%; b: cutoff value = 2.0, sensit...

ROC curve of PDVFS and cutoff point for prediction of the development of aspiration pneumonia.

Satoshi Tomita (403444)
Tomoko Oeda (233773)
Atsushi Umemura (158649)
Masayuki Kohsaka (403445)
Kwiyoung Park (571065)
Kenji Yamamoto (233783)
Hiroshi Sugiyama (14595)
Hideyuki Sawada (233770)

June 2018

ROC curve of PDVFS and cutoff point for prediction of the development of aspiration pneumonia.</p

ROC curve for the prediction of survival at the 12-month time point.

Joonsang Lee (795630)
Shivali Narang (795631)
Juan Martinez (4033448)
Ganesh Rao (795632)
Arvind Rao (208219)

September 2015

The x-axis is the false- positive rate, 1 –specificity; the y-axis is the true- positive rate, se...

ROC curve for linear regression model calculated with the parameters age, average platelet count on day 10, average pump flow rate on day 10, minimum partial pressure of oxygen on day 10, and average pH on day 10 after the start of veno-venous extracorporeal membrane oxygenation.

Bärbel Kieninger (11502108)
Magdalena Kilger (3450395)
Maik Foltan (668125)
Michael Gruber (318913)
Dirk Lunz (668127)
Thomas Dienemann (3415745)
Stephan Schmid (3608621)
Bernhard Graf (522352)
Clemens Wiest (13165305)
Matthias Lubnow (668123)
Thomas Müller (3554)
Bernd Salzberger (801373)
Wulf Schneider-Brachert (320442)
Martin Kieninger (11502096)

January 2023

The yellow arrow is at a separation value of 0.85 with a sensitivity of 61.9 and a specificity of 97...

Volume status for predicting mortality.

Szu-Chun Hung (114864)
Yao-Ping Lin (114868)
Hsin-Lei Huang (383499)
Hsiao-Fung Pu (383500)
Der-Cherng Tarng (114877)

March 2013

The receiver operating characteristic (ROC) curve for prediction of all-cause mortality construct...

ROC curve for determining the cut-off value of serum CMV viral load for the development of (i) CMV end organ diseases (EODs) (left) and (ii) Disseminated CMV EODs (right).

Avirup Chakraborty (2218096)
Tanmay Mahapatra (484660)
Sanchita Mahapatra (509306)
Sabbir Ansari (2218090)
Sattik Siddhanta (2218099)
Siwalik Banerjee (2218102)
Dipanjan Banerjee (1445326)
Rathindra Nath Sarkar (2218093)
Subhashish Kamal Guha (2218087)
Nilanjan Chakraborty (604285)

February 2015

ROC curve for determining the cut-off value of serum CMV viral load for the development of (i) CM...

The optimal cut-off levels of 91H relative expression were determined based on the largest of sensitivity and specificity by receiver operating characteristic curve (ROC) analysis for overall survival.

Qiwen Deng (530955)
Bangshun He (119526)
Tianyi Gao (119544)
Yuqin Pan (119528)
Huiling Sun (530956)
Yeqiong Xu (119533)
Rui Li (4631)
Houqun Ying (603739)
Feng Wang (44414)
Xian Liu (191882)
Jie Chen (5892)
Shukui Wang (119550)

July 2014

The optimal cut-off levels of 91H relative expression were determined based on the largest of sen...

ROC curves for the determination of the overall performance of the assay and the optimal cut-off value for each mutant's index.

Velizar Shivarov (464941)
Milena Ivanova (464942)
Elissaveta Naumova (95112)

June 2014

ROC curves for the determination of the overall performance of the assay and the optimal cut-off ...

Receiver operating characteristic (ROC) curve defining cutoff levels predicting outcomes in eligible trials with molecularly selected patients in terms of the progression-free survival-hazard ratio (PFS-HR) (A) and the odds ratio for the overall response (B).

Katsuyuki Hotta (78500)
Yuka Kato (9286)
Natasha Leighl (703141)
Nagio Takigawa (144711)
Rabab Mohamed Gaafar (703142)
Hiroe Kayatani (703143)
Taizo Hirata (309169)
Kadoaki Ohashi (703144)
Toshio Kubo (703145)
Masahiro Tabata (144716)
Mitsune Tanimoto (78508)
Katsuyuki Kiura (78507)

March 2015

The most suitable cutoff was defined as that closest to the upper left corner. A, A PFS-HR of 0.6...

Receiver Operating Characteristic (ROC) curve for the best cut-off point of Glasgow Coma Scale (GCS) that predicts survival.

Mohamed A. Al-Ali (14192745)
David O. Alao (11442104)
Fikri M. Abu-Zidan (8638308)

November 2022

Receiver Operating Characteristic (ROC) curve for the best cut-off point of Glasgow Coma Scale (GCS)...

Optimal cut-off, area under the ROC-curve (Area), and diagnostic sensitivity and specificity of statistically significant biochemical markers.

Marie Åsberg (374799)
Åke Nygren (374800)
Rosario Leopardi (374801)
Gunnar Rylander (374802)
Ulla Peterson (374803)
Lukas Wilczek (374804)
Håkan Källmén (374806)
Mirjam Ekstedt (374808)
Torbjörn Åkerstedt (3343088)
Mats Lekander (226776)
Rolf Ekman (369536)

February 2013

Optimal cut-off, area under the ROC-curve (Area), and diagnostic sensitivity and specificity of s...

Prognostic ROC curves: a method for representing the overall discriminative capacity of binary markers with right-censored time-to-event endpoints

Combescure, Christophe
Perneger, Thomas
Weber, Damien
Daurès, Jean-Pierre
Foucher, Yohann

January 2014

Survival curves are a popular tool for representing the association between a binary marker and the ...

ROC curve showing optimal cut-off value of 3 mm (sensitivity, 0.795; specificity, 0.61).

Hajime Ushigome (6321017)
Yosuke Fukunaga (4056700)
Toshiya Nagasaki (3438119)
Takashi Akiyoshi (4056697)
Tsuyoshi Konishi (4056691)
Yoshiya Fujimoto (4056703)
Satoshi Nagayama (105355)
Masashi Ueno (4056694)

February 2019

ROC curve showing optimal cut-off value of 3 mm (sensitivity, 0.795; specificity, 0.61).</p

Defining an Optimal Cut-Point Value in ROC Analysis: An Alternative Approach

Ünal, İlker

ROC curve analysis is often applied to measure the diagnostic accuracy of a biomarker. The analysis ...

Kaplan Meier curves showing the cumulative survival for those with and without PAE and for pulmonary artery diameter quartiles.

Juan P. de-Torres (400034)
Ana Ezponda (4951021)
Ana B. Alcaide (400035)
Arantza Campo (400039)
Juan Berto (2621371)
Jessica Gonzalez (3621353)
Javier J. Zulueta (400042)
Ciro Casanova (357425)
Luisa Elena Rodriguez-Delgado (5142602)
Bartolome R. Celli (204834)
Gorka Bastarrika (400037)

April 2018

Kaplan Meier curves showing the cumulative survival for those with and without PAE and for pulmon...

ROC curves of the RCSI score and CTSI score in predicting the mortality.

Haotong Xu (197706)
Lukas Ebner (403773)
Shiming Jiang (629653)
Yi Wu (197719)
Andreas Christe (403772)
Shaoxiang Zhang (197722)
Xiaoming Zhang (104062)
Zhulin Luo (403774)
Fuzhou Tian (403775)

September 2014

(a: cutoff value = 4.0, sensitivity = 82.11%, specificity = 96.91%; b: cutoff value = 2.0, sensit...

ROC curve of PDVFS and cutoff point for prediction of the development of aspiration pneumonia.

Satoshi Tomita (403444)
Tomoko Oeda (233773)
Atsushi Umemura (158649)
Masayuki Kohsaka (403445)
Kwiyoung Park (571065)
Kenji Yamamoto (233783)
Hiroshi Sugiyama (14595)
Hideyuki Sawada (233770)

June 2018

ROC curve of PDVFS and cutoff point for prediction of the development of aspiration pneumonia.</p

ROC curve for the prediction of survival at the 12-month time point.

Joonsang Lee (795630)
Shivali Narang (795631)
Juan Martinez (4033448)
Ganesh Rao (795632)
Arvind Rao (208219)

September 2015

The x-axis is the false- positive rate, 1 –specificity; the y-axis is the true- positive rate, se...

ROC curve for linear regression model calculated with the parameters age, average platelet count on day 10, average pump flow rate on day 10, minimum partial pressure of oxygen on day 10, and average pH on day 10 after the start of veno-venous extracorporeal membrane oxygenation.

Bärbel Kieninger (11502108)
Magdalena Kilger (3450395)
Maik Foltan (668125)
Michael Gruber (318913)
Dirk Lunz (668127)
Thomas Dienemann (3415745)
Stephan Schmid (3608621)
Bernhard Graf (522352)
Clemens Wiest (13165305)
Matthias Lubnow (668123)
Thomas Müller (3554)
Bernd Salzberger (801373)
Wulf Schneider-Brachert (320442)
Martin Kieninger (11502096)

January 2023

The yellow arrow is at a separation value of 0.85 with a sensitivity of 61.9 and a specificity of 97...

Volume status for predicting mortality.

Szu-Chun Hung (114864)
Yao-Ping Lin (114868)
Hsin-Lei Huang (383499)
Hsiao-Fung Pu (383500)
Der-Cherng Tarng (114877)

March 2013

The receiver operating characteristic (ROC) curve for prediction of all-cause mortality construct...

ROC curve for determining the cut-off value of serum CMV viral load for the development of (i) CMV end organ diseases (EODs) (left) and (ii) Disseminated CMV EODs (right).

Avirup Chakraborty (2218096)
Tanmay Mahapatra (484660)
Sanchita Mahapatra (509306)
Sabbir Ansari (2218090)
Sattik Siddhanta (2218099)
Siwalik Banerjee (2218102)
Dipanjan Banerjee (1445326)
Rathindra Nath Sarkar (2218093)
Subhashish Kamal Guha (2218087)
Nilanjan Chakraborty (604285)

February 2015

ROC curve for determining the cut-off value of serum CMV viral load for the development of (i) CM...

Survival curves according to the optimal cut-off value derived by ROC analysis for preoperative pulmonary vascular resistance (PVR).

Abstract

Extracted data

Survival curves according to the optimal cut-off value derived by ROC analysis for preoperative pulmonary vascular resistance (PVR).

Abstract

Extracted data

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