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

Michael Burns

School of the Art Institute of Chicago

ORCID: 0000-0002-5474-705X

Also affiliated with University of Michigan, Michigan United, Michigan Medicine

MedicineComputer ScienceEngineering

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 6%percentile
0.251Author 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.

Medical data sharing and synthetic clinical data generation – maximizing biomedical resource utilization and minimizing participant re-identification risks

npj Digital Medicine(2025)10.1038/s41746-025-01935-1
Top 60%
0.251DataRank
Top 60%4 citations

Ruth Cassidy, Joseph Nanni, Yuxuan Wang, Yipeng Liu, Ming‐Yi Tang +7 more

Papers

Driven by 7 papers — median percentile 40. Top paper: “Medical data sharing and synthetic clinical data generation – maximizing biomedical resource utilization and minimizing participant re-identification risks”.

Medical data sharing and synthetic clinical data generation – maximizing biomedical resource utilization and minimizing participant re-identification risks

npj Digital Medicine(2025)10.1038/s41746-025-01935-1
Top 60%
0.251DataRank
Top 60%4 citations

Ruth Cassidy, Joseph Nanni, Yuxuan Wang, Yipeng Liu, Ming‐Yi Tang +7 more

Re‐evaluating expanding intravenous catheters in medical practice

Health Science Reports(2021)10.1002/hsr2.318
N/A
0DataRank · unranked
3 citations

Rishabh Tennankore, Ariella Shikanov, Leonard A. Mermel, Brian J. Love, Michael Burns +1 more

Machine Learning for the Prediction of Procedural Case Durations Developed Using a Large Multicenter Database: Algorithm Development and Validation Study

JMIR AI(2023)10.2196/44909
N/A
0DataRank · unranked
18 citations

Andrew Bishara, Michael Burns, Stuart Solomon, Matthew A. Corriere, Michael R. Mathis +1 more

Neural Machine Translation–Based Automated Current Procedural Terminology Classification System Using Procedure Text: Development and Validation Study

JMIR Formative Research(2021)10.2196/22461
N/A
0DataRank · unranked
16 citations

Michael Burns, Sai Saradha Kalidaikurichi Lakshmanan, Yaokun Hu, V. G. Vinod Vydiswaran, Hyeon Joo

Strengthening Discovery and Application of Artificial Intelligence in Anesthesiology: A Report from the Anesthesia Research Council

Anesthesiology(2025)10.1097/aln.0000000000005326
N/A
0DataRank · unranked
15 citations

Michael Burns, Richard H. Epstein, Ira Hofer, Patrick Tighe, J. Arias Delgado +6 more

Generative AI costs in large healthcare systems, an example in revenue cycle

npj Digital Medicine(2025)10.1038/s41746-025-01971-x
N/A
0DataRank · unranked
10 citations

Ssu-Ying Chen, Chu-An Tsai, John Vandervest, Balaji Pandian, Paige Nong +4 more

Development and Testing of a Data Capture Device for Use With Clinical Incentive Spirometers: Testing and Usability Study

JMIR Biomedical Engineering(2023)10.2196/46653
N/A
0DataRank · unranked
2 citations

Anik Sinha, Alexander Hoffmann, Zewen Wu, Tomas Medina Inchauste, Aaron Retsky +4 more