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

Clara Mosquera-Lopez

Artificial Intelligence in Medicine (Canada)

ORCID: 0000-0003-1586-2490
MedicineComputer ScienceHealth ProfessionsBiochemistry, Genetics and Molecular Biology

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
1.4Author 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.

Quantifying the impact of physical activity on future glucose trends using machine learning

iScience(2022)10.1016/j.isci.2022.103888
Top 15%
1.4DataRank
Top 15%43 citations

Clara Mosquera-Lopez, Gavin Young, Joseph El Youssef, Jessica R. Castle, Peter G. Jacobs +1 more

Papers

Driven by 9 papers — median percentile 85. Top paper: “Quantifying the impact of physical activity on future glucose trends using machine learning”.

Quantifying the impact of physical activity on future glucose trends using machine learning

iScience(2022)10.1016/j.isci.2022.103888
Top 15%
1.4DataRank
Top 15%43 citations

Clara Mosquera-Lopez, Gavin Young, Joseph El Youssef, Jessica R. Castle, Peter G. Jacobs +1 more

Integrating metabolic expenditure information from wearable fitness sensors into an AI-augmented automated insulin delivery system: a randomised clinical trial

The Lancet Digital Health(2023)10.1016/s2589-7500(23)00112-7
N/A
1.1DataRank · unranked
33 citations

Navid Resalat, Wade Hilts, Gavin Young, Joseph Leitschuh, Joseph Pinsonault +10 more

Enabling fully automated insulin delivery through meal detection and size estimation using Artificial Intelligence

npj Digital Medicine(2023)10.1038/s41746-023-00783-1
N/A
0.598DataRank · unranked
53 citations

Leah M. Wilson, Joseph El Youssef, Wade Hilts, Joseph Leitschuh, Deborah Branigan +5 more

Identifying and Intervening on Glucose Patterns in Multivariate Data Using Block-Based Recurrence Quantification Analysis

Journal of Diabetes Science and Technology(2025)10.1177/19322968251386058
N/A
0.104DataRank · unranked
1 citations

Clara Mosquera-Lopez, Wade Hilts, Joseph Leitschuh, Robert H. Dodier, Deborah Branigan +6 more

Predicting and Preventing Nocturnal Hypoglycemia in Type 1 Diabetes Using Big Data Analytics and Decision Theoretic Analysis

Diabetes Technology & Therapeutics(2020)10.1089/dia.2019.0458
N/A
0DataRank · unranked
45 citations

Robert H. Dodier, Nichole S. Tyler, Leah M. Wilson, Joseph El Youssef, Jessica R. Castle +2 more

An AI-enabled dual-hormone model predictive control algorithm that delivers insulin and pramlintide

IFAC-PapersOnLine(2025)10.1016/j.ifacol.2025.06.011
N/A
0DataRank · unranked
0 citations

Wade Hilts, Robert H. Dodier, Joseph Leitschuh, Jae Eom, Deborah Branigan +5 more

Measuring glucose at the site of insulin delivery with a redox-mediated sensor

Biosensors and Bioelectronics(2020)10.1016/j.bios.2020.112221
N/A
0DataRank · unranked
10 citations

Nichole S. Tyler, Scott M. Vanderwerf, Clara Mosquera-Lopez, Thomas L. Seidl, Robert S. Cargill +7 more

Modeling risk of hypoglycemia during and following physical activity in people with type 1 diabetes using explainable mixed-effects machine learning

Computers in Biology and Medicine(2023)10.1016/j.compbiomed.2023.106670
N/A
0DataRank · unranked
32 citations

Katrina Ramsey, Valentina Roquemen-Echeverri, Peter G. Jacobs, Clara Mosquera-Lopez

Combining uncertainty-aware predictive modeling and a bedtimeSmart Snackintervention to prevent nocturnal hypoglycemia in people with type 1 diabetes on multiple daily injections

Journal of the American Medical Informatics Association(2023)10.1093/jamia/ocad196
N/A
0DataRank · unranked
15 citations

Valentina Roquemen-Echeverri, Nichole S. Tyler, Susana R. Patton, Mark A. Clements, Corby K. Martin +7 more