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Christoph Haarburger

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Frontiers in Computational Neuroscience|November 30, 2019
Robustness of Radiomics for Survival Prediction of Brain Tumor Patients Depending on Resection StatusLeon Weninger, Christoph Haarburger, Dorit Merhof
Radiology|November 14, 2018
Radiomic versus Convolutional Neural Networks Analysis for Classification of Contrast-enhancing Lesions at Multiparametric Breast MRIDaniel Truhn, Simone Schrading, Christoph Haarburger, et al.
Scientific Reports|July 31, 2020
Radiomics feature reproducibility under inter-rater variability in segmentations of CT imagesChristoph Haarburger, Gustav Müller-Franzes, Leon Weninger, et al.
European Radiology Experimental|April 7, 2020
Multiphase CT-based prediction of Child-Pugh classification: a machine learning approachJohannes Thüring, Oliver Rippel, Christoph Haarburger, et al.
Science Advances|December 3, 2020
Breaking medical data sharing boundaries by using synthesized radiographsTianyu Han, Sven Nebelung, Christoph Haarburger, et al.
Diagnostics (Basel, Switzerland)|February 25, 2022
Reliability as a Precondition for Trust-Segmentation Reliability Analysis of Radiomic Features Improves Survival PredictionGustav Müller-Franzes, Sven Nebelung, Justus Schock, et al.
Nature Communications|July 15, 2021
Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalizationTianyu Han, Sven Nebelung, Federico Pedersoli, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|March 9, 2017
Towards an algorithm for automatic accelerometer-based pulse presence detection during cardiopulmonary resuscitationKiran Dellimore, Ralph Wijshoff, Christoph Haarburger, et al.
NPJ Digital Medicine|October 24, 2024
Medical large language models are susceptible to targeted misinformation attacksTianyu Han, Sven Nebelung, Firas Khader, et al.
Radiology|October 3, 2023
Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for TransformersFiras Khader, Gustav Müller-Franzes, Tianci Wang, et al.
Pageof 2

Showing results (1-10 of 15) with videos related to

Sort By:
Pageof 2
Frontiers in Computational Neuroscience|November 30, 2019
Robustness of Radiomics for Survival Prediction of Brain Tumor Patients Depending on Resection StatusLeon Weninger, Christoph Haarburger, Dorit Merhof
Radiology|November 14, 2018
Radiomic versus Convolutional Neural Networks Analysis for Classification of Contrast-enhancing Lesions at Multiparametric Breast MRIDaniel Truhn, Simone Schrading, Christoph Haarburger, et al.
Scientific Reports|July 31, 2020
Radiomics feature reproducibility under inter-rater variability in segmentations of CT imagesChristoph Haarburger, Gustav Müller-Franzes, Leon Weninger, et al.
European Radiology Experimental|April 7, 2020
Multiphase CT-based prediction of Child-Pugh classification: a machine learning approachJohannes Thüring, Oliver Rippel, Christoph Haarburger, et al.
Science Advances|December 3, 2020
Breaking medical data sharing boundaries by using synthesized radiographsTianyu Han, Sven Nebelung, Christoph Haarburger, et al.
Diagnostics (Basel, Switzerland)|February 25, 2022
Reliability as a Precondition for Trust-Segmentation Reliability Analysis of Radiomic Features Improves Survival PredictionGustav Müller-Franzes, Sven Nebelung, Justus Schock, et al.
Nature Communications|July 15, 2021
Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalizationTianyu Han, Sven Nebelung, Federico Pedersoli, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|March 9, 2017
Towards an algorithm for automatic accelerometer-based pulse presence detection during cardiopulmonary resuscitationKiran Dellimore, Ralph Wijshoff, Christoph Haarburger, et al.
NPJ Digital Medicine|October 24, 2024
Medical large language models are susceptible to targeted misinformation attacksTianyu Han, Sven Nebelung, Firas Khader, et al.
Radiology|October 3, 2023
Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for TransformersFiras Khader, Gustav Müller-Franzes, Tianci Wang, et al.
Pageof 2