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

Scott A. Crossley

Vanderbilt University

ORCID: 0000-0002-5148-0273

Also affiliated with Vanderbilt Health

Computer SciencePsychologySocial Sciences

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 4%percentile
0.829Author 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.

Employing computational linguistics techniques to identify limited patient health literacy: Findings from the ECLIPPSE study

Health Services Research(2020)10.1111/1475-6773.13560
Top 24%
0.829DataRank
Top 24%23 citations

Renu Balyan, Scott A. Crossley, Danielle S. McNamara, Jennifer Y. Liu, Andrew J. Karter +1 more

Papers

Driven by 3 papers — median percentile 76. Top paper: “Employing computational linguistics techniques to identify limited patient health literacy: Findings from the ECLIPPSE study”.

Employing computational linguistics techniques to identify limited patient health literacy: Findings from the ECLIPPSE study

Health Services Research(2020)10.1111/1475-6773.13560
Top 24%
0.829DataRank
Top 24%23 citations

Renu Balyan, Scott A. Crossley, Danielle S. McNamara, Jennifer Y. Liu, Andrew J. Karter +1 more

Challenges and solutions to employing natural language processing and machine learning to measure patients’ health literacy and physician writing complexity: The ECLIPPSE study

Journal of Biomedical Informatics(2020)10.1016/j.jbi.2020.103658
N/A
0DataRank · unranked
23 citations

Renu Balyan, Andrew J. Karter, Scott A. Crossley, Wagahta Semere, Nicholas D. Duran +7 more

Predicting the readability of physicians’ secure messages to improve health communication using novel linguistic features: Findings from the ECLIPPSE study

Journal of Communications In Healthcare(2020)10.1080/17538068.2020.1822726
N/A
0DataRank · unranked
23 citations

Renu Balyan, Jennifer Y. Liu, Andrew J. Karter, Danielle S. McNamara, Dean Schillinger +1 more