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

Talid Sinno

University of Pennsylvania

ORCID: 0000-0003-2489-1613

Also affiliated with Philadelphia University

EngineeringMaterials SciencePhysics and Astronomy

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
1.2Author 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.

Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission

PLoS ONE(2020)10.1371/journal.pone.0242166
Top 17%
1.2DataRank
Top 17%26 citations

Carrie A. Sims, Talid Sinno, Scott L. Diamond, Evan J. Tsiklidis

Papers

Driven by 8 papers — median percentile 83. Top paper: “Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission”.

Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission

PLoS ONE(2020)10.1371/journal.pone.0242166
Top 17%
1.2DataRank
Top 17%26 citations

Carrie A. Sims, Talid Sinno, Scott L. Diamond, Evan J. Tsiklidis

Anti-GPVI Fab reveals distinct roles for GPVI signaling in the first platelet layer and subsequent layers during microfluidic clotting on collagen with or without tissue factor

Thrombosis Research(2022)10.1016/j.thromres.2022.08.018
N/A
0.373DataRank · unranked
11 citations

Kevin Timothy Trigani, Kaushik N. Shankar, Jennifer Crossen, Yue Liu, Talid Sinno +2 more

Thrombosis and hemodynamics: External and intrathrombus gradients

Current Opinion in Biomedical Engineering(2021)10.1016/j.cobme.2021.100316
N/A
0DataRank · unranked
10 citations

Kaushik N. Shankar, Talid Sinno, Scott L. Diamond, Noelia Grande Gutiérrez

A three-dimensional multiscale model for the prediction of thrombus growth under flow with single-platelet resolution

PLoS Computational Biology(2022)10.1371/journal.pcbi.1009850
N/A
0DataRank · unranked
31 citations

Yiyuan Zhang, Talid Sinno, Scott L. Diamond, Kaushik N. Shankar

Predicting risk for trauma patients using static and dynamic information from the MIMIC III database

PLoS ONE(2022)10.1371/journal.pone.0262523
N/A
0DataRank · unranked
12 citations

Talid Sinno, Scott L. Diamond, Evan J. Tsiklidis

Development of a parallel multiscale 3D model for thrombus growth under flow

Frontiers in Physics(2023)10.3389/fphy.2023.1256462
N/A
0DataRank · unranked
5 citations

Scott L. Diamond, Talid Sinno, Kaushik N. Shankar

Multiscale simulations that incorporate patient-specific neural network models of platelet calcium signaling predict diverse thrombotic outcomes under flow

PLoS Computational Biology(2025)10.1371/journal.pcbi.1013085
N/A
0DataRank · unranked
2 citations

Talid Sinno, Scott L. Diamond, Kaushik N. Shankar

Thrombin spatial distribution determines protein C activation during hemostasis and thrombosis

Blood(2021)10.1182/blood.2021014338
N/A
0DataRank · unranked
19 citations

Chelsea Matzko, Jie Wu, Charles T. Esmon, Talid Sinno, Lawrence F. Brass +3 more