🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Katharina Hoebel

Harvard University

ORCID: 0000-0002-1881-7065

Also affiliated with Harvard–MIT Division of Health Sciences and Technology, Dana-Farber Cancer Institute, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts Institute of Technology

MedicineComputer Science

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 2%percentile
3.3Author DataRank

Indexed papers

2in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 2 indexed papers attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Top data-sharing exemplar

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

Radiomics Repeatability Pitfalls in a Scan-Rescan MRI Study of Glioblastoma

Radiology Artificial Intelligence(2020)10.1148/ryai.2020190199
Top 8%
2.8DataRank
Top 8%53 citations

Jay Patel, Andrew Beers, Ken Chang, Praveer Singh, James M. Brown +6 more

Papers

Driven by 12 papers — median percentile 76. Top paper: “Radiomics Repeatability Pitfalls in a Scan-Rescan MRI Study of Glioblastoma”.

Radiomics Repeatability Pitfalls in a Scan-Rescan MRI Study of Glioblastoma

Radiology Artificial Intelligence(2020)10.1148/ryai.2020190199
Top 8%
2.8DataRank
Top 8%53 citations

Jay Patel, Andrew Beers, Ken Chang, Praveer Singh, James M. Brown +6 more

Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast Density

Journal of the American College of Radiology(2020)10.1016/j.jacr.2020.05.015
N/A
0.593DataRank · unranked
51 citations

Andrew Beers, Laura Brink, Jay Patel, Praveer Singh, Nishanth Arun +11 more

Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation

Radiology Artificial Intelligence(2023)10.1148/ryai.220231
Top 40%
0.476DataRank
Top 40%11 citations

Christopher P. Bridge, Sara Ahmed, Oluwatosin Akintola, Caroline Chung, Raymond Y. Huang +11 more

Abnormal vascular structure and function within brain metastases is linked to pembrolizumab resistance

Neuro-Oncology(2023)10.1093/neuonc/noad236
N/A
0.323DataRank · unranked
6 citations

Kevin W Lou, Anita Giobbie‐Hurder, Ken Chang, Mishka Gidwani, Katharina Hoebel +38 more

DeepNeuro: an open-source deep learning toolbox for neuroimaging

Neuroinformatics(2020)10.1007/s12021-020-09477-5
N/A
0.208DataRank · unranked
3 citations

James M. Brown, Ken Chang, Katharina Hoebel, Jay Patel, Bruce R. Rosen +6 more

Inconsistent Partitioning and Unproductive Feature Associations Yield Idealized Radiomic Models

Radiology(2022)10.1148/radiol.220715
N/A
0DataRank · unranked
29 citations

Ken Chang, Jay Biren Patel, Katharina Hoebel, Syed Rakin Ahmed, Praveer Singh +3 more

Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging

npj Digital Medicine(2020)10.1038/s41746-020-0255-1
N/A
0DataRank · unranked
135 citations

Ken Chang, Ben Bearce, Connie Y. Chang, Ambrose J. Huang, J. Peter Campbell +9 more

Structural and functional vascular dysfunction within brain metastases is linked to pembrolizumab inefficacy

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.08.25.554868
N/A
0DataRank · unranked
0 citations

Kevin W Lou, Anita Giobbie‐Hurder, Ken Chang, Mishka Gidwani, Katharina Hoebel +38 more

Assessing the Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging

Radiology Artificial Intelligence(2021)10.1148/ryai.2021200267
N/A
0DataRank · unranked
277 citations

Nathan Gaw, Praveer Singh, Ken Chang, Mehak Aggarwal, Bryan Chen +8 more

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results

arXiv (Cornell University)(2021)10.48550/arxiv.2112.10074
N/A
0DataRank · unranked
7 citations

Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard McKinley, Michael Rebsamen +87 more

Improving the repeatability of deep learning models with Monte Carlo dropout

npj Digital Medicine(2022)10.1038/s41746-022-00709-3
N/A
0DataRank · unranked
95 citations

Katharina Hoebel, Christopher P. Bridge, Brian Befano, Sílvia de Sanjosé, Didem Egemen +5 more

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation – Analysis of Ranking Scores and Benchmarking Results

The Journal of Machine Learning for Biomedical Imaging(2022)10.59275/j.melba.2022-354b
N/A
0DataRank · unranked
53 citations

Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard McKinley, Michael Rebsamen +87 more