ROC curves for the top performing model compared to individual feature predictions.

Guy Witberg (6335546)
Ygal Plakht (6236060)
Tamir Bental (800113)
Becca S. Feldman (635241)
Maya Leventer-Roberts (4232806)
Amos Levi (4031684)
Hagit Gabay (6335549)
Ran Balicer (4232812)
Yariv Gerber (686409)
Ran Kornowski (540888)

February 2019

ROC curves and c-statistics of the ischaemic (left) and bleeding (right) prediction models.</p

ROC curves comparing the ML performance with three datasets groups (the thin line represents each iteration’s ROC, and the thick line is the mean ROC).

Tarun Gangil (14266311)
Krishna Sharan (530343)
B. Dinesh Rao (14266314)
Krishnamoorthy Palanisamy (9676622)
Biswaroop Chakrabarti (14266317)
Rajagopal Kadavigere (14266320)

December 2022

The column of the model utilizing only clinical data from our previous study [6] is included for com...

ROC Curve of the linear regression equation proposed as a prediction model for AHI.

Evangelos Kaimakamis (2551480)
Venetia Tsara (2551471)
Charalambos Bratsas (2551477)
Lazaros Sichletidis (2551474)
Charalambos Karvounis (2551483)
Nikolaos Maglaveras (2551486)

March 2016

ROC Curve of the linear regression equation proposed as a prediction model for AHI.</p

ROC curve for the best model found on the reduced feature set (discovery).

Ting Hu (110925)
Karoliina Oksanen (4903168)
Weidong Zhang (68880)
Ed Randell (4903165)
Andrew Furey (567520)
Guang Sun (305123)
Guangju Zhai (110167)

March 2018

ROC curve for the best model found on the reduced feature set (discovery).</p

Precision recall curves for the top performing model compared to individual feature predictions.

Robert Hammond (3631525)
Rodoniki Athanasiadou (250841)
Silvia Curado (60275)
Yindalon Aphinyanaphongs (3526454)
Courtney Abrams (6619631)
Mary Jo Messito (6619634)
Rachel Gross (6585113)
Michelle Katzow (6619637)
Melanie Jay (6291920)
Narges Razavian (6619640)
Brian Elbel (2838662)

April 2019

Precision recall curves for the top performing model compared to individual feature predictions.</p

ROC curve for the best model found on the reduced feature set (replication).

Ting Hu (110925)
Karoliina Oksanen (4903168)
Weidong Zhang (68880)
Ed Randell (4903165)
Andrew Furey (567520)
Guang Sun (305123)
Guangju Zhai (110167)

March 2018

ROC curve for the best model found on the reduced feature set (replication).</p

ROC curve for logistic regression, the best model found on the reduced feature set (discovery).

Ting Hu (110925)
Karoliina Oksanen (4903168)
Weidong Zhang (68880)
Ed Randell (4903165)
Andrew Furey (567520)
Guang Sun (305123)
Guangju Zhai (110167)

March 2018

ROC curve for logistic regression, the best model found on the reduced feature set (discovery).</...

ROC curves for the best result in Experiment 4 (Non correlated features at 97%).

M. Milagro Fernández-Carrobles (820011)
Gloria Bueno (773393)
Oscar Déniz (2206690)
Jesús Salido (820012)
Marcial García-Rojo (820013)
Lucía González-López (820014)

October 2015

ROC curves for the best result in Experiment 4 (Non correlated features at 97%).</p

Comparison of the performance of the models using area under the curve (AUC) of ROC.

Arjun Parthipan (6307895)
Imon Banerjee (6307898)
Keith Humphreys (28187)
Steven M. Asch (6307901)
Catherine Curtin (6307904)
Ian Carroll (415150)
Tina Hernandez-Boussard (4013)

February 2019

Comparison of the performance of the models using area under the curve (AUC) of ROC.</p

ROC curve and prediction parameters for optimal thresholds in all tested methods.

Octavio Espinosa (220816)
Konstantinos Mitsopoulos (509736)
Jarle Hakas (215012)
Frances Pearl (57486)
Marketa Zvelebil (13881)

January 2014

ROC curve and prediction parameters for optimal thresholds in all tested methods.</p

ROC curves of the model under non-feature selection, feature selection, and mixed sampling.

Huizhong Lin (14044381)
Yutao Xue (12451975)
Kaizhi Chen (14192740)
Shangping Zhong (14192743)
Lianglong Chen (5715980)

November 2022

ROC curves of the model under non-feature selection, feature selection, and mixed sampling.</p

Comparison of various prediction methods in terms of the area under the ROC curve (AUC).

Bernd Lütkenhöner (486490)
Türker Basel (486491)

November 2013

Comparison of various prediction methods in terms of the area under the ROC curve (AUC).</p

Comparison between ROC curves obtained with the marginal and integrated model.

Filippo Trentini (433274)
Yuan Ji (5702)
Takayuki Iwamoto (190293)
Yuan Qi (71013)
Lajos Pusztai (78763)
Peter Müller (433275)

July 2013

Comparison between ROC curves obtained with the marginal and integrated model.</p

ROC curves of the PR (a) and CR (b) model for the best and worst training (solid) and the validation set (dashed).

Remy Klaassen (3903154)
Ruben T. H. M. Larue (4421839)
Banafsche Mearadji (5979446)
Stephanie O. van der Woude (5979449)
Jaap Stoker (34500)
Philippe Lambin (19883)
Hanneke W. M. van Laarhoven (457158)

November 2018

ROC curves of the PR (a) and CR (b) model for the best and worst training (solid) and the validation...

ROC curve for the best classification models resulting from the LOO validation (ranking based on the AUC obtained for each classifier).

Diana de la Iglesia (649447)
Miguel García-Remesal (649448)
Alberto Anguita (649449)
Miguel Muñoz-Mármol (649450)
Casimir Kulikowski (649451)
Víctor Maojo (649452)

October 2014

ROC curve for the best classification models resulting from the LOO validation (ranking based on ...

ROC curves for prediction models.

Guy Witberg (6335546)
Ygal Plakht (6236060)
Tamir Bental (800113)
Becca S. Feldman (635241)
Maya Leventer-Roberts (4232806)
Amos Levi (4031684)
Hagit Gabay (6335549)
Ran Balicer (4232812)
Yariv Gerber (686409)
Ran Kornowski (540888)

February 2019

ROC curves and c-statistics of the ischaemic (left) and bleeding (right) prediction models.</p

ROC curves comparing the ML performance with three datasets groups (the thin line represents each iteration’s ROC, and the thick line is the mean ROC).

Tarun Gangil (14266311)
Krishna Sharan (530343)
B. Dinesh Rao (14266314)
Krishnamoorthy Palanisamy (9676622)
Biswaroop Chakrabarti (14266317)
Rajagopal Kadavigere (14266320)

December 2022

The column of the model utilizing only clinical data from our previous study [6] is included for com...

ROC Curve of the linear regression equation proposed as a prediction model for AHI.

Evangelos Kaimakamis (2551480)
Venetia Tsara (2551471)
Charalambos Bratsas (2551477)
Lazaros Sichletidis (2551474)
Charalambos Karvounis (2551483)
Nikolaos Maglaveras (2551486)

March 2016

ROC Curve of the linear regression equation proposed as a prediction model for AHI.</p

ROC curve for the best model found on the reduced feature set (discovery).

Ting Hu (110925)
Karoliina Oksanen (4903168)
Weidong Zhang (68880)
Ed Randell (4903165)
Andrew Furey (567520)
Guang Sun (305123)
Guangju Zhai (110167)

March 2018

ROC curve for the best model found on the reduced feature set (discovery).</p

Precision recall curves for the top performing model compared to individual feature predictions.

Robert Hammond (3631525)
Rodoniki Athanasiadou (250841)
Silvia Curado (60275)
Yindalon Aphinyanaphongs (3526454)
Courtney Abrams (6619631)
Mary Jo Messito (6619634)
Rachel Gross (6585113)
Michelle Katzow (6619637)
Melanie Jay (6291920)
Narges Razavian (6619640)
Brian Elbel (2838662)

April 2019

Precision recall curves for the top performing model compared to individual feature predictions.</p

ROC curve for the best model found on the reduced feature set (replication).

Ting Hu (110925)
Karoliina Oksanen (4903168)
Weidong Zhang (68880)
Ed Randell (4903165)
Andrew Furey (567520)
Guang Sun (305123)
Guangju Zhai (110167)

March 2018

ROC curve for the best model found on the reduced feature set (replication).</p

ROC curve for logistic regression, the best model found on the reduced feature set (discovery).

Ting Hu (110925)
Karoliina Oksanen (4903168)
Weidong Zhang (68880)
Ed Randell (4903165)
Andrew Furey (567520)
Guang Sun (305123)
Guangju Zhai (110167)

March 2018

ROC curve for logistic regression, the best model found on the reduced feature set (discovery).</...

ROC curves for the best result in Experiment 4 (Non correlated features at 97%).

M. Milagro Fernández-Carrobles (820011)
Gloria Bueno (773393)
Oscar Déniz (2206690)
Jesús Salido (820012)
Marcial García-Rojo (820013)
Lucía González-López (820014)

October 2015

ROC curves for the best result in Experiment 4 (Non correlated features at 97%).</p

Comparison of the performance of the models using area under the curve (AUC) of ROC.

Arjun Parthipan (6307895)
Imon Banerjee (6307898)
Keith Humphreys (28187)
Steven M. Asch (6307901)
Catherine Curtin (6307904)
Ian Carroll (415150)
Tina Hernandez-Boussard (4013)

February 2019

Comparison of the performance of the models using area under the curve (AUC) of ROC.</p

ROC curve and prediction parameters for optimal thresholds in all tested methods.

Octavio Espinosa (220816)
Konstantinos Mitsopoulos (509736)
Jarle Hakas (215012)
Frances Pearl (57486)
Marketa Zvelebil (13881)

January 2014

ROC curve and prediction parameters for optimal thresholds in all tested methods.</p

ROC curves of the model under non-feature selection, feature selection, and mixed sampling.

Huizhong Lin (14044381)
Yutao Xue (12451975)
Kaizhi Chen (14192740)
Shangping Zhong (14192743)
Lianglong Chen (5715980)

November 2022

ROC curves of the model under non-feature selection, feature selection, and mixed sampling.</p

Comparison of various prediction methods in terms of the area under the ROC curve (AUC).

Bernd Lütkenhöner (486490)
Türker Basel (486491)

November 2013

Comparison of various prediction methods in terms of the area under the ROC curve (AUC).</p

Comparison between ROC curves obtained with the marginal and integrated model.

Filippo Trentini (433274)
Yuan Ji (5702)
Takayuki Iwamoto (190293)
Yuan Qi (71013)
Lajos Pusztai (78763)
Peter Müller (433275)

July 2013

Comparison between ROC curves obtained with the marginal and integrated model.</p

ROC curves of the PR (a) and CR (b) model for the best and worst training (solid) and the validation set (dashed).

Remy Klaassen (3903154)
Ruben T. H. M. Larue (4421839)
Banafsche Mearadji (5979446)
Stephanie O. van der Woude (5979449)
Jaap Stoker (34500)
Philippe Lambin (19883)
Hanneke W. M. van Laarhoven (457158)

November 2018

ROC curves of the PR (a) and CR (b) model for the best and worst training (solid) and the validation...

ROC curve for the best classification models resulting from the LOO validation (ranking based on the AUC obtained for each classifier).

Diana de la Iglesia (649447)
Miguel García-Remesal (649448)
Alberto Anguita (649449)
Miguel Muñoz-Mármol (649450)
Casimir Kulikowski (649451)
Víctor Maojo (649452)

October 2014

ROC curve for the best classification models resulting from the LOO validation (ranking based on ...

ROC curves for prediction models.

Guy Witberg (6335546)
Ygal Plakht (6236060)
Tamir Bental (800113)
Becca S. Feldman (635241)
Maya Leventer-Roberts (4232806)
Amos Levi (4031684)
Hagit Gabay (6335549)
Ran Balicer (4232812)
Yariv Gerber (686409)
Ran Kornowski (540888)

February 2019

ROC curves and c-statistics of the ischaemic (left) and bleeding (right) prediction models.</p

ROC curves comparing the ML performance with three datasets groups (the thin line represents each iteration’s ROC, and the thick line is the mean ROC).

Tarun Gangil (14266311)
Krishna Sharan (530343)
B. Dinesh Rao (14266314)
Krishnamoorthy Palanisamy (9676622)
Biswaroop Chakrabarti (14266317)
Rajagopal Kadavigere (14266320)

December 2022

The column of the model utilizing only clinical data from our previous study [6] is included for com...

ROC Curve of the linear regression equation proposed as a prediction model for AHI.

Evangelos Kaimakamis (2551480)
Venetia Tsara (2551471)
Charalambos Bratsas (2551477)
Lazaros Sichletidis (2551474)
Charalambos Karvounis (2551483)
Nikolaos Maglaveras (2551486)

March 2016

ROC Curve of the linear regression equation proposed as a prediction model for AHI.</p

ROC curves for the top performing model compared to individual feature predictions.

Abstract

Extracted data

ROC curves for the top performing model compared to individual feature predictions.

Abstract

Extracted data

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