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

Natalie Baughan

Henry Ford Health System

ORCID: 0000-0002-3219-9291

Also affiliated with University of Chicago

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 3%percentile
1.6Author DataRank

Indexed papers

5in 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 5 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.

Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons

Journal of Medical Imaging(2023)10.1117/1.jmi.10.6.061105
Top 32%
0.610DataRank
Top 32%9 citations

Natalie Baughan, Kyle J. Myers, Karen Drukker, Judy Wawira Gichoya, Brad Bower +9 more

Papers

Driven by 8 papers — median percentile 49. Top paper: “Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons”.

Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons

Journal of Medical Imaging(2023)10.1117/1.jmi.10.6.061105
Top 32%
0.610DataRank
Top 32%9 citations

Natalie Baughan, Kyle J. Myers, Karen Drukker, Judy Wawira Gichoya, Brad Bower +9 more

Sequestration of imaging studies in MIDRC: stratified sampling to balance demographic characteristics of patients in a multi-institutional data commons

Journal of Medical Imaging(2023)10.1117/1.jmi.10.6.064501
Top 45%
0.416DataRank
Top 45%15 citations

Heather M. Whitney, Karen Drukker, Berkman Sahiner, Tingting Hu, Grace Hyun J. Kim +4 more

MIDRC-MetricTree: a decision tree-based tool for recommending performance metrics in artificial intelligence-assisted medical image analysis

Journal of Medical Imaging(2024)10.1117/1.jmi.11.2.024504
Top 51%
0.347DataRank
Top 51%6 citations

Berkman Sahiner, Tingting Hu, Grace Hyun J. Kim, Heather M. Whitney, Natalie Baughan +4 more

Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center Open Data Commons

arXiv (Cornell University)(2023)10.48550/arxiv.2303.10501
Top 78%
0.104DataRank
Top 78%1 citations

Natalie Baughan, Kyle J. Myers, Karen Drukker, Judy Wawira Gichoya, Brad Bower +9 more

MIDRC mRALE Mastermind Grand Challenge: AI to predict COVID severity on chest radiographs

Journal of Medical Imaging(2025)10.1117/1.jmi.12.2.024505
Top 78%
0.104DataRank
Top 78%1 citations

Karen Drukker, Lubomir M. Hadjiiski, Carol C. Wu, Jayashree Kalpathy-Cramer, George Shih +9 more

Radiomic and deep learning characterization of breast parenchyma on full field digital mammograms and specimen radiographs: a pilot study of a potential cancer field effect

Journal of Medical Imaging(2023)10.1117/1.jmi.10.4.044501
N/A
0DataRank · unranked
2 citations

Hui Li, Lan Li, Matthew Embury, Isaiah Yim, Gary J. Whitman +4 more

Temporal Machine Learning Analysis of Prior Mammograms for Breast Cancer Risk Prediction

Cancers(2023)10.3390/cancers15072141
N/A
0DataRank · unranked
12 citations

Kayla Robinson, Lan Li, Natalie Baughan, C. W. Chan, Matthew Embury +5 more

Past, Present, and Future of Machine Learning and Artificial Intelligence for Breast Cancer Screening

Journal of Breast Imaging(2022)10.1093/jbi/wbac052
N/A
0DataRank · unranked
17 citations

Lindsay Douglas, Maryellen L. Giger, Natalie Baughan