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Luke Oakden-Rayner

Showing results (1-10 of 21) with videos related to

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Radiology. Artificial Intelligence|May 3, 2021
The Rebirth of CAD: How Is Modern AI Different from the CAD We Know?Luke Oakden-Rayner
Academic Radiology|November 11, 2019
Exploring Large-scale Public Medical Image DatasetsLuke Oakden-Rayner
Radiology. Artificial Intelligence|May 3, 2021
Guidance for Interventional Trials Involving Artificial IntelligenceHugh Harvey, Luke Oakden-Rayner
The Lancet. Digital Health|October 29, 2021
The false hope of current approaches to explainable artificial intelligence in health careMarzyeh Ghassemi, Luke Oakden-Rayner, Andrew L Beam
International Journal of Epidemiology|June 6, 2018
Medical journals should embrace preprints to address the reproducibility crisisLuke Oakden-Rayner, Andrew L Beam, Lyle J Palmer
Proceedings of the ACM Conference on Health, Inference, and Learning|November 16, 2020
Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical ImagingLuke Oakden-Rayner, Jared Dunnmon, Gustavo Carneiro, et al.
Stroke|January 18, 2019
Deep Learning Natural Language Processing Successfully Predicts the Cerebrovascular Cause of Transient Ischemic Attack-Like PresentationsStephen Bacchi, Luke Oakden-Rayner, Toby Zerner, et al.
Academic Radiology|May 5, 2019
Deep Learning in the Prediction of Ischaemic Stroke Thrombolysis Functional Outcomes: A Pilot StudyStephen Bacchi, Toby Zerner, Luke Oakden-Rayner, et al.
Journal of Medical Imaging and Radiation Oncology|July 12, 2021
Assessing the accuracy of <sup>68</sup> Ga-PSMA PET/CT compared with MRI in the initial diagnosis of prostate malignancy: A cohort analysis of 114 consecutive patientsFelix Paterson, Michelle Nottage, Michael Kitchener, et al.
Internal Medicine Journal|October 23, 2020
Machine learning in the prediction of medical inpatient length of stayStephen Bacchi, Yiran Tan, Luke Oakden-Rayner, et al.
Pageof 3

Showing results (1-10 of 21) with videos related to

Sort By:
Pageof 3
Radiology. Artificial Intelligence|May 3, 2021
The Rebirth of CAD: How Is Modern AI Different from the CAD We Know?Luke Oakden-Rayner
Academic Radiology|November 11, 2019
Exploring Large-scale Public Medical Image DatasetsLuke Oakden-Rayner
Radiology. Artificial Intelligence|May 3, 2021
Guidance for Interventional Trials Involving Artificial IntelligenceHugh Harvey, Luke Oakden-Rayner
The Lancet. Digital Health|October 29, 2021
The false hope of current approaches to explainable artificial intelligence in health careMarzyeh Ghassemi, Luke Oakden-Rayner, Andrew L Beam
International Journal of Epidemiology|June 6, 2018
Medical journals should embrace preprints to address the reproducibility crisisLuke Oakden-Rayner, Andrew L Beam, Lyle J Palmer
Proceedings of the ACM Conference on Health, Inference, and Learning|November 16, 2020
Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical ImagingLuke Oakden-Rayner, Jared Dunnmon, Gustavo Carneiro, et al.
Stroke|January 18, 2019
Deep Learning Natural Language Processing Successfully Predicts the Cerebrovascular Cause of Transient Ischemic Attack-Like PresentationsStephen Bacchi, Luke Oakden-Rayner, Toby Zerner, et al.
Academic Radiology|May 5, 2019
Deep Learning in the Prediction of Ischaemic Stroke Thrombolysis Functional Outcomes: A Pilot StudyStephen Bacchi, Toby Zerner, Luke Oakden-Rayner, et al.
Journal of Medical Imaging and Radiation Oncology|July 12, 2021
Assessing the accuracy of <sup>68</sup> Ga-PSMA PET/CT compared with MRI in the initial diagnosis of prostate malignancy: A cohort analysis of 114 consecutive patientsFelix Paterson, Michelle Nottage, Michael Kitchener, et al.
Internal Medicine Journal|October 23, 2020
Machine learning in the prediction of medical inpatient length of stayStephen Bacchi, Yiran Tan, Luke Oakden-Rayner, et al.
Pageof 3