Katharina Hoebel - Concepedia

Author

Katharina Hoebel

Athinoula A. Martinos Center for Biomedical Imaging ORCID

Also Known As

Hoebel, Katharina, Hoebel, Katharina V., Hoebel, Katharina Viktoria, K Hoebel, K.V. Hoebel, Katharina Hoebel, Katharina V. Hoebel, Katharina Viktoria Hoebel

Publications

936

Citations

H-Index

Concepts

All Affiliations

Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Massachusetts Institute of Technology Harvard University Harvard–MIT Division of Health Sciences and Technology

About

Katharina Hoebel is an author at Athinoula A. Martinos Center for Biomedical Imaging specializing in engineering, medical image computing, and data science.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	6	6	234
2	Health Sciences	3	3	101
3	Biostatistics	3	3	97
4	Medicine	2	2	83
5	Biomedical Engineering	1	1	21

Katharina Hoebel

Publications

860

Citations

H-Index

Page 1

	Year	Citations
Assessing the Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging Nishanth Arun, Nathan Gaw, Praveer Singh, Radiology Artificial Intelligence	2021	247
Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging Matthew Li, Ken Chang, Ben Bearce, npj Digital Medicine	2020	132
Improving the repeatability of deep learning models with Monte Carlo dropout Andréanne Lemay, Katharina Hoebel, Christopher P. Bridge, npj Digital Medicine	2022	78
Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture Michael A. Silva, Jay Patel, Vasileios K. Kavouridis, World Neurosurgery Artificial IntelligenceEngineeringMachine LearningData ScienceMachine Learning Model	2019	66
Radiomics Repeatability Pitfalls in a Scan-Rescan MRI Study of Glioblastoma Katharina Hoebel, Jay Patel, Andrew Beers, Radiology Artificial Intelligence	2020	51
Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast Density Ken Chang, Andrew Beers, Laura Brink, Journal of the American College of Radiology Artificial IntelligenceEngineeringMachine LearningData ScienceDeep Learning	2020	50
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation – Analysis of Ranking Scores and Benchmarking Results Raghav Mehta, Angelos Filos, Ujjwal Baid, The Journal of Machine Learning for Biomedical Imaging	2022	46
Assessing the (Un)Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging Nishanth Arun, Nathan Gaw, Praveer Singh, EngineeringMachine LearningDiagnostic ImagingImage ClassificationImage Analysis	2020	41
An exploration of uncertainty information for segmentation quality assessment Katharina Hoebel, Vincent Andrearczyk, Andrew Beers, Medical Image SegmentationEngineeringMachine LearningUncertain DataUncertainty Modeling	2020	39
Inconsistent Partitioning and Unproductive Feature Associations Yield Idealized Radiomic Models Mishka Gidwani, Ken Chang, Jay Patel, Radiology	2022	28

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