Comparison of The Area Under the Receiver Operating Characteristic Curves (AUCs) in Internal Validation Set (N = 461).

Comparison of AIC, AUC, and ROC curves for logistic regression models.

Hiro Takahashi (65723)
Kimie Sai (616024)
Yoshiro Saito (195372)
Nahoko Kaniwa (616025)
Yasuhiro Matsumura (187249)
Tetsuya Hamaguchi (616026)
Yasuhiro Shimada (616027)
Atsushi Ohtsu (223901)
Takayuki Yoshino (616028)
Toshihiko Doi (616029)
Haruhiro Okuda (616030)
Risa Ichinohe (616031)
Anna Takahashi (475164)
Ayano Doi (616032)
Yoko Odaka (616033)
Misuzu Okuyama (616034)
Nagahiro Saijo (616035)
Jun-ichi Sawada (616036)
Hiromi Sakamoto (212872)
Teruhiko Yoshida (65725)

August 2014

(A) Parameters of each model. (B) The ROC curve of a model consisting of rs9351963+MMC+ Amrubicin...

Areas Under the Receiver Operating Characteristic Curve (AUROC), and Precision Recall Curve (AUPRC) in 10-fold cross validation with 50 replications of multiple logistic regression classifiers.

Ian E. R. Waudby-Smith (5348984)
Nam Tran (267065)
Joel A. Dubin (740170)
Joon Lee (75830)

June 2018

Areas Under the Receiver Operating Characteristic Curve (AUROC), and Precision Recall Curve (AUPR...

Receiver-operating characteristic (ROC) curves for the artificial neural network (ANN) and logistic regression bootstrap analyses (see the text for a description of the bootstrap procedure)

Navdeep Tangri (93209)
David Ansell (93210)
David Naimark (93211)

December 2011

The curves represent the average curves for the 20 ANN and 20 logistic models. The area under the RO...

Comparison of The Area Under the Receiver Operating Characteristic Curves (AUCs) in External Validation Set (N = 2,500).

Ying-Jui Chang (345484)
Min-Li Yeh (345485)
Yu-Chuan Li (306790)
Chien-Yeh Hsu (345486)
Chao-Cheng Lin (345488)
Meng-Shiuan Hsu (345490)
Wen-Ta Chiu (319104)

February 2013

The comparison of AUCs between different variable groups of artificial neural network (ANN-1, ANN...

Comparison of The Area Under the Receiver Operating Characteristic Curves (AUCs) in Training Set (N = 927).

Ying-Jui Chang (345484)
Min-Li Yeh (345485)
Yu-Chuan Li (306790)
Chien-Yeh Hsu (345486)
Chao-Cheng Lin (345488)
Meng-Shiuan Hsu (345490)
Wen-Ta Chiu (319104)

February 2013

All variables were included in artificial neural network (ANN) model and 7 variables were include...

Comparison of ANN, LR and Scoring in External Validation, % (N = 2,500).

Ying-Jui Chang (345484)
Min-Li Yeh (345485)
Yu-Chuan Li (306790)
Chien-Yeh Hsu (345486)
Chao-Cheng Lin (345488)
Meng-Shiuan Hsu (345490)
Wen-Ta Chiu (319104)

February 2013

aMean±SE,bcomparison with ANN model.Group 1: all variables.Group 3: medical ...

ROC curves of ANN and LR prediction models in the validation group.

Chong-Jian Wang (139783)
Yu-Qian Li (139786)
Ling Wang (56577)
Lin-Lin Li (139788)
Yi-Rui Guo (139792)
Ling-Yun Zhang (139795)
Mei-Xi Zhang (139799)
Rong-Hai Bie (139803)

August 2012

Areas under ROC curves were 0.86 and 0.68 for ANN and LR models, respectively. Area under ROC cur...

ROC curve for artificial neural networks and logistic regression analysis in identifying SDI≥1 and SDI≥5.

Cristina Eller-Vainicher (340190)
Iacopo Chiodini (340191)
Ivana Santi (340192)
Marco Massarotti (340193)
Luca Pietrogrande (340194)
Elisa Cairoli (340195)
Paolo Beck-Peccoz (340196)
Matteo Longhi (340197)
Valter Galmarini (340198)
Giorgio Gandolini (340199)
Maurizio Bevilacqua (340200)
Enzo Grossi (50473)

February 2013

The ANN AUC is significantly superior to LR AUC both in identifying SDI≥1 (p<0.01) (A) and SDI≥5 ...

Comparison of the area under the receiver operating characteristic curves (AUC) between control and preperimetric PA group.

Hae Ri Yum (2600932)
Shin Hae Park (681484)
Hae-Young Lopilly Park (766061)
Sun Young Shin (1571716)

April 2016

Comparison of the area under the receiver operating characteristic curves (AUC) between control a...

Fig 3 -

Hehe Bai (10904101)
Huan Li (120482)
Xiaojing Nie (302128)
Yanqin Yao (17020929)
Xiaonian Han (6208460)
Jinping Wang (1297071)
Lirong Peng (2819821)

September 2023

The ROC curves in the training (A), internal validation (B) and external validation (C) groups. The ...

Receiver-operating characteristic analysis of the artificial neural network in comparison with logistic regression model, as well as qHBsAg and HBV DNA.

Ming-Hua Zheng (138448)
Wai-Kay Seto (310865)
Ke-Qing Shi (138450)
Danny Ka-Ho Wong (310866)
James Fung (310867)
Ivan Fan-Ngai Hung (310871)
Daniel Yee-Tak Fong (346339)
John Chi-Hang Yuen (310868)
Teresa Tong (575676)
Ching-Lung Lai (310874)
Man-Fung Yuen (310877)

June 2014

ANN, artificial neural network. LRM, logistic regression model. AUROC, area under the receiver op...

AUROC comparison of three ANN models (A) and results of internal validation of the NNC prediction model (B).

Wenliang Zhu (205320)
Xuan Kan (643413)

October 2014

UNN: untransformed neural network; TNN: transformed neural network; NNC: neural network cascade. ...

Areas under the receiver-operating-characteristic curves.

Yael Silberberg (454638)
Martin Kupiec (70559)
Roded Sharan (23003)

March 2014

Areas under the curves (AUC) obtained in a 10-fold cross-validation setting. The AUC is averaged ...

Pairwise comparison of the area under the receiver operating characteristic curves (AUC) between the thickness and OIAC measurements in the SN quadrant, ST quadrant, and global average of mRNFL.

Min Sun (115484)
Zhiqiang Zhang (1522858)
Chiyuan Ma (702577)
Suihua Chen (4117339)
Xinjian Chen (324533)

June 2017

Pairwise comparison of the area under the receiver operating characteristic curves (AUC) between ...

Diagnostic performance of ANN model and scoring systems with receiver operating characteristic curve analysis and density plot.

Jihoon G. Yoon (5165897)
JoonNyung Heo (5165912)
Minkyu Kim (275255)
Yu Jin Park (1510411)
Min Hyuk Choi (5165909)
Jaewoo Song (780027)
Kangsan Wyi (5165906)
Hakbeen Kim (5165894)
Olivier Duchenne (5165903)
Soowon Eom (5165900)
Yury Tsoy (4571662)

May 2018

(A) Training (Set 1): ANN model shows the best performance among the four diagnostic classifiers....

Comparison of AIC, AUC, and ROC curves for logistic regression models.

Hiro Takahashi (65723)
Kimie Sai (616024)
Yoshiro Saito (195372)
Nahoko Kaniwa (616025)
Yasuhiro Matsumura (187249)
Tetsuya Hamaguchi (616026)
Yasuhiro Shimada (616027)
Atsushi Ohtsu (223901)
Takayuki Yoshino (616028)
Toshihiko Doi (616029)
Haruhiro Okuda (616030)
Risa Ichinohe (616031)
Anna Takahashi (475164)
Ayano Doi (616032)
Yoko Odaka (616033)
Misuzu Okuyama (616034)
Nagahiro Saijo (616035)
Jun-ichi Sawada (616036)
Hiromi Sakamoto (212872)
Teruhiko Yoshida (65725)

August 2014

(A) Parameters of each model. (B) The ROC curve of a model consisting of rs9351963+MMC+ Amrubicin...

Areas Under the Receiver Operating Characteristic Curve (AUROC), and Precision Recall Curve (AUPRC) in 10-fold cross validation with 50 replications of multiple logistic regression classifiers.

Ian E. R. Waudby-Smith (5348984)
Nam Tran (267065)
Joel A. Dubin (740170)
Joon Lee (75830)

June 2018

Areas Under the Receiver Operating Characteristic Curve (AUROC), and Precision Recall Curve (AUPR...

Receiver-operating characteristic (ROC) curves for the artificial neural network (ANN) and logistic regression bootstrap analyses (see the text for a description of the bootstrap procedure)

Navdeep Tangri (93209)
David Ansell (93210)
David Naimark (93211)

December 2011

The curves represent the average curves for the 20 ANN and 20 logistic models. The area under the RO...

Comparison of The Area Under the Receiver Operating Characteristic Curves (AUCs) in External Validation Set (N = 2,500).

Ying-Jui Chang (345484)
Min-Li Yeh (345485)
Yu-Chuan Li (306790)
Chien-Yeh Hsu (345486)
Chao-Cheng Lin (345488)
Meng-Shiuan Hsu (345490)
Wen-Ta Chiu (319104)

February 2013

The comparison of AUCs between different variable groups of artificial neural network (ANN-1, ANN...

Comparison of The Area Under the Receiver Operating Characteristic Curves (AUCs) in Training Set (N = 927).

Ying-Jui Chang (345484)
Min-Li Yeh (345485)
Yu-Chuan Li (306790)
Chien-Yeh Hsu (345486)
Chao-Cheng Lin (345488)
Meng-Shiuan Hsu (345490)
Wen-Ta Chiu (319104)

February 2013

All variables were included in artificial neural network (ANN) model and 7 variables were include...

Comparison of ANN, LR and Scoring in External Validation, % (N = 2,500).

Ying-Jui Chang (345484)
Min-Li Yeh (345485)
Yu-Chuan Li (306790)
Chien-Yeh Hsu (345486)
Chao-Cheng Lin (345488)
Meng-Shiuan Hsu (345490)
Wen-Ta Chiu (319104)

February 2013

aMean±SE,bcomparison with ANN model.Group 1: all variables.Group 3: medical ...

ROC curves of ANN and LR prediction models in the validation group.

Chong-Jian Wang (139783)
Yu-Qian Li (139786)
Ling Wang (56577)
Lin-Lin Li (139788)
Yi-Rui Guo (139792)
Ling-Yun Zhang (139795)
Mei-Xi Zhang (139799)
Rong-Hai Bie (139803)

August 2012

Areas under ROC curves were 0.86 and 0.68 for ANN and LR models, respectively. Area under ROC cur...

ROC curve for artificial neural networks and logistic regression analysis in identifying SDI≥1 and SDI≥5.

Cristina Eller-Vainicher (340190)
Iacopo Chiodini (340191)
Ivana Santi (340192)
Marco Massarotti (340193)
Luca Pietrogrande (340194)
Elisa Cairoli (340195)
Paolo Beck-Peccoz (340196)
Matteo Longhi (340197)
Valter Galmarini (340198)
Giorgio Gandolini (340199)
Maurizio Bevilacqua (340200)
Enzo Grossi (50473)

February 2013

The ANN AUC is significantly superior to LR AUC both in identifying SDI≥1 (p<0.01) (A) and SDI≥5 ...

Comparison of the area under the receiver operating characteristic curves (AUC) between control and preperimetric PA group.

Hae Ri Yum (2600932)
Shin Hae Park (681484)
Hae-Young Lopilly Park (766061)
Sun Young Shin (1571716)

April 2016

Comparison of the area under the receiver operating characteristic curves (AUC) between control a...

Fig 3 -

Hehe Bai (10904101)
Huan Li (120482)
Xiaojing Nie (302128)
Yanqin Yao (17020929)
Xiaonian Han (6208460)
Jinping Wang (1297071)
Lirong Peng (2819821)

September 2023

The ROC curves in the training (A), internal validation (B) and external validation (C) groups. The ...

Receiver-operating characteristic analysis of the artificial neural network in comparison with logistic regression model, as well as qHBsAg and HBV DNA.

Ming-Hua Zheng (138448)
Wai-Kay Seto (310865)
Ke-Qing Shi (138450)
Danny Ka-Ho Wong (310866)
James Fung (310867)
Ivan Fan-Ngai Hung (310871)
Daniel Yee-Tak Fong (346339)
John Chi-Hang Yuen (310868)
Teresa Tong (575676)
Ching-Lung Lai (310874)
Man-Fung Yuen (310877)

June 2014

ANN, artificial neural network. LRM, logistic regression model. AUROC, area under the receiver op...

AUROC comparison of three ANN models (A) and results of internal validation of the NNC prediction model (B).

Wenliang Zhu (205320)
Xuan Kan (643413)

October 2014

UNN: untransformed neural network; TNN: transformed neural network; NNC: neural network cascade. ...

Areas under the receiver-operating-characteristic curves.

Yael Silberberg (454638)
Martin Kupiec (70559)
Roded Sharan (23003)

March 2014

Areas under the curves (AUC) obtained in a 10-fold cross-validation setting. The AUC is averaged ...

Pairwise comparison of the area under the receiver operating characteristic curves (AUC) between the thickness and OIAC measurements in the SN quadrant, ST quadrant, and global average of mRNFL.

Min Sun (115484)
Zhiqiang Zhang (1522858)
Chiyuan Ma (702577)
Suihua Chen (4117339)
Xinjian Chen (324533)

June 2017

Pairwise comparison of the area under the receiver operating characteristic curves (AUC) between ...

Diagnostic performance of ANN model and scoring systems with receiver operating characteristic curve analysis and density plot.

Jihoon G. Yoon (5165897)
JoonNyung Heo (5165912)
Minkyu Kim (275255)
Yu Jin Park (1510411)
Min Hyuk Choi (5165909)
Jaewoo Song (780027)
Kangsan Wyi (5165906)
Hakbeen Kim (5165894)
Olivier Duchenne (5165903)
Soowon Eom (5165900)
Yury Tsoy (4571662)

May 2018

(A) Training (Set 1): ANN model shows the best performance among the four diagnostic classifiers....

Comparison of AIC, AUC, and ROC curves for logistic regression models.

Hiro Takahashi (65723)
Kimie Sai (616024)
Yoshiro Saito (195372)
Nahoko Kaniwa (616025)
Yasuhiro Matsumura (187249)
Tetsuya Hamaguchi (616026)
Yasuhiro Shimada (616027)
Atsushi Ohtsu (223901)
Takayuki Yoshino (616028)
Toshihiko Doi (616029)
Haruhiro Okuda (616030)
Risa Ichinohe (616031)
Anna Takahashi (475164)
Ayano Doi (616032)
Yoko Odaka (616033)
Misuzu Okuyama (616034)
Nagahiro Saijo (616035)
Jun-ichi Sawada (616036)
Hiromi Sakamoto (212872)
Teruhiko Yoshida (65725)

August 2014

(A) Parameters of each model. (B) The ROC curve of a model consisting of rs9351963+MMC+ Amrubicin...

Areas Under the Receiver Operating Characteristic Curve (AUROC), and Precision Recall Curve (AUPRC) in 10-fold cross validation with 50 replications of multiple logistic regression classifiers.

Ian E. R. Waudby-Smith (5348984)
Nam Tran (267065)
Joel A. Dubin (740170)
Joon Lee (75830)

June 2018

Areas Under the Receiver Operating Characteristic Curve (AUROC), and Precision Recall Curve (AUPR...

Receiver-operating characteristic (ROC) curves for the artificial neural network (ANN) and logistic regression bootstrap analyses (see the text for a description of the bootstrap procedure)

Navdeep Tangri (93209)
David Ansell (93210)
David Naimark (93211)

December 2011

The curves represent the average curves for the 20 ANN and 20 logistic models. The area under the RO...

Comparison of The Area Under the Receiver Operating Characteristic Curves (AUCs) in Internal Validation Set (N = 461).

Abstract

Extracted data

Comparison of The Area Under the Receiver Operating Characteristic Curves (AUCs) in Internal Validation Set (N = 461).

Abstract

Extracted data

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