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

Christian F. Baumgartner

University of Lucerne

ORCID: 0000-0002-3629-4384

Also affiliated with University of Tübingen

Computer ScienceMedicine

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
1.5Author DataRank

Indexed papers

1in 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 1 indexed paper 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.

Accuracy and longitudinal reproducibility of quantitative femorotibial cartilage measures derived from automated U-Net-based segmentation of two different MRI contrasts: data from the osteoarthritis initiative healthy reference cohort

Magnetic Resonance Materials in Physics Biology and Medicine(2020)10.1007/s10334-020-00889-7
Top 14%
1.5DataRank
Top 14%46 citations

F. Eckstein, Jana Kemnitz, Christian F. Baumgartner, Ender Konukoğlu, David Fuerst +2 more

Papers

Driven by 4 papers — median percentile 86. Top paper: “Accuracy and longitudinal reproducibility of quantitative femorotibial cartilage measures derived from automated U-Net-based segmentation of two different MRI contrasts: data from the osteoarthritis initiative healthy reference cohort”.

Accuracy and longitudinal reproducibility of quantitative femorotibial cartilage measures derived from automated U-Net-based segmentation of two different MRI contrasts: data from the osteoarthritis initiative healthy reference cohort

Magnetic Resonance Materials in Physics Biology and Medicine(2020)10.1007/s10334-020-00889-7
Top 14%
1.5DataRank
Top 14%46 citations

F. Eckstein, Jana Kemnitz, Christian F. Baumgartner, Ender Konukoğlu, David Fuerst +2 more

Detection of Differences in Longitudinal Cartilage Thickness Loss Using a Deep‐Learning Automated Segmentation Algorithm: Data From the Foundation for the National Institutes of Health Biomarkers Study of the Osteoarthritis Initiative

Arthritis Care & Research(2020)10.1002/acr.24539
N/A
0.903DataRank · unranked
39 citations

Akshay Chaudhari, David Fuerst, Martin Gaisberger, Jana Kemnitz, Christian F. Baumgartner +4 more

Evaluation of an automated laminar cartilage T2 relaxation time analysis method in an early osteoarthritis model

Skeletal Radiology(2024)10.1007/s00256-024-04786-1
N/A
0.351DataRank · unranked
8 citations

S. Maschek, Anna Wisser, Jana Eder, Christian F. Baumgartner, Akshay Chaudhari +3 more

K2S Challenge: From Undersampled K-Space to Automatic Segmentation

Bioengineering(2023)10.3390/bioengineering10020267
N/A
0DataRank · unranked
22 citations

Upasana Bharadwaj, Kenneth T. Gao, Rupsa Bhattacharjee, Felix G. Gassert, Johanna Luitjens +18 more