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Ben Glocker

Showing results (91-100 of 132) with videos related to

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JAMA Network Open|November 30, 2020
Evaluation of Deep Learning to Augment Image-Guided Radiotherapy for Head and Neck and Prostate CancersOzan Oktay, Jay Nanavati, Anton Schwaighofer, et al.
Journal of Neurotrauma|January 14, 2020
Relationship between Measures of Cerebrovascular Reactivity and Intracranial Lesion Progression in Acute Traumatic Brain Injury Patients: A CENTER-TBI StudyFrançois Mathieu, Frederick A Zeiler, Ari Ercole, et al.
BMJ Open|October 5, 2022
Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy studyLaura Satchwell, Linda Wedlake, Emily Greenlay, et al.
Plos One|November 29, 2017
Regional brain morphometry in patients with traumatic brain injury based on acute- and chronic-phase magnetic resonance imagingChristian Ledig, Konstantinos Kamnitsas, Juha Koikkalainen, et al.
BMC Cancer|May 19, 2023
Multi-vendor evaluation of artificial intelligence as an independent reader for double reading in breast cancer screening on 275,900 mammogramsNisha Sharma, Annie Y Ng, Jonathan J James, et al.
BMJ Open|May 23, 2023
Investigating the characteristics and correlates of systemic inflammation after traumatic brain injury: the TBI-BraINFLAMM studyLucia M Li, Amanda Heslegrave, Eyal Soreq, et al.
Journal of Neurotrauma|April 22, 2020
Impact of Antithrombotic Agents on Radiological Lesion Progression in Acute Traumatic Brain Injury: A CENTER-TBI Propensity-Matched Cohort AnalysisFrançois Mathieu, Helge Güting, Benjamin Gravesteijn, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|December 9, 2014
Quantifying progression of multiple sclerosis via classification of depth videosPeter Kontschieder, Jonas F Dorn, Cecily Morrison, et al.
Insights Into Imaging|February 16, 2024
Curation of myeloma observational study MALIMAR using XNAT: solving the challenges posed by real-world dataSimon J Doran, Theo Barfoot, Linda Wedlake, et al.
Ophthalmology Science|April 28, 2023
Exploring Healthy Retinal Aging with Deep LearningMartin J Menten, Robbie Holland, Oliver Leingang, et al.
Pageof 14

Showing results (91-100 of 132) with videos related to

Sort By:
Pageof 14
JAMA Network Open|November 30, 2020
Evaluation of Deep Learning to Augment Image-Guided Radiotherapy for Head and Neck and Prostate CancersOzan Oktay, Jay Nanavati, Anton Schwaighofer, et al.
Journal of Neurotrauma|January 14, 2020
Relationship between Measures of Cerebrovascular Reactivity and Intracranial Lesion Progression in Acute Traumatic Brain Injury Patients: A CENTER-TBI StudyFrançois Mathieu, Frederick A Zeiler, Ari Ercole, et al.
BMJ Open|October 5, 2022
Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before and after treatment (MALIMAR): protocol for a cross-sectional diagnostic test accuracy studyLaura Satchwell, Linda Wedlake, Emily Greenlay, et al.
Plos One|November 29, 2017
Regional brain morphometry in patients with traumatic brain injury based on acute- and chronic-phase magnetic resonance imagingChristian Ledig, Konstantinos Kamnitsas, Juha Koikkalainen, et al.
BMC Cancer|May 19, 2023
Multi-vendor evaluation of artificial intelligence as an independent reader for double reading in breast cancer screening on 275,900 mammogramsNisha Sharma, Annie Y Ng, Jonathan J James, et al.
BMJ Open|May 23, 2023
Investigating the characteristics and correlates of systemic inflammation after traumatic brain injury: the TBI-BraINFLAMM studyLucia M Li, Amanda Heslegrave, Eyal Soreq, et al.
Journal of Neurotrauma|April 22, 2020
Impact of Antithrombotic Agents on Radiological Lesion Progression in Acute Traumatic Brain Injury: A CENTER-TBI Propensity-Matched Cohort AnalysisFrançois Mathieu, Helge Güting, Benjamin Gravesteijn, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|December 9, 2014
Quantifying progression of multiple sclerosis via classification of depth videosPeter Kontschieder, Jonas F Dorn, Cecily Morrison, et al.
Insights Into Imaging|February 16, 2024
Curation of myeloma observational study MALIMAR using XNAT: solving the challenges posed by real-world dataSimon J Doran, Theo Barfoot, Linda Wedlake, et al.
Ophthalmology Science|April 28, 2023
Exploring Healthy Retinal Aging with Deep LearningMartin J Menten, Robbie Holland, Oliver Leingang, et al.
Pageof 14