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

Massimiliano Russo

Brigham and Women's Hospital

ORCID: 0000-0003-4953-9341

Also affiliated with Harvard University, The Ohio State University, University of Naples Federico II

EngineeringMathematics

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 100%percentile
0Author DataRank

Indexed papers

0in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 10 papers. Top paper: “Targeted learning with an undersmoothed LASSO propensity score model for large-scale covariate adjustment in health-care database studies”.

Targeted learning with an undersmoothed LASSO propensity score model for large-scale covariate adjustment in health-care database studies

American Journal of Epidemiology(2024)10.1093/aje/kwae023
N/A
0.406DataRank · unranked
14 citations

Mark van der Laan, Susan Gruber, Xu Shi, Hana Lee, Sarah K. Dutcher +7 more

Testing interventions to reduce clinical inertia in the treatment of hypertension: rationale and design of a pragmatic randomized controlled trial

American Heart Journal(2023)10.1016/j.ahj.2023.11.005
N/A
0.394DataRank · unranked
6 citations

Sushama Kattinakere Sreedhara, Wendy Wood, Elad Yom‐Tov, Daniel M. Horn, Melissa Hoover +9 more

Comparing Fourteen Behavioral Science Electronic Health Record Deprescribing Tools in Older Adults: NUDGE ‐ EHR Adaptive Trial

Journal of the American Geriatrics Society(2025)10.1111/jgs.19609
N/A
0.262DataRank · unranked
4 citations

Thomas Isaac, Lorenzo Trippa, Robert J. Glynn, Massimiliano Russo, Punam Anand Keller +11 more

Note on targeted learning with an undersmoothed Lasso propensity score model for large-scale covariate adjustment in health care database studies

American Journal of Epidemiology(2025)10.1093/aje/kwaf024
N/A
0.165DataRank · unranked
2 citations

Mark van der Laan, Susan Gruber, Xu Shi, Hana Lee, Sarah K. Dutcher +7 more

A Cautious Use of Auxiliary Outcomes for Decision-Making in Randomized Clinical Trials

Bayesian Analysis(2025)10.1214/26-ba1596
N/A
0DataRank · unranked
0 citations

Steffen Ventz, Lorenzo Trippa, Massimiliano Russo

Inference in response‐adaptive clinical trials when the enrolled population varies over time

Biometrics(2021)10.1111/biom.13582
N/A
0DataRank · unranked
3 citations

Steffen Ventz, Victoria Wang, Lorenzo Trippa, Massimiliano Russo

Potential Drug Dose‐Specific Adverse Three‐Drug Combinations: A US Insurance Claims Data‐Based Study

Pharmacoepidemiology and Drug Safety(2025)10.1002/pds.70199
N/A
0DataRank · unranked
0 citations

Alfred Xuyang Sun, C. W. Chiang, Y. Yang, Katherine M. Hunold, Jie Xu +8 more

Trends in the Antibiotic Treatment of Acute Sinusitis: 2003–2020

PEDIATRICS(2023)10.1542/peds.2022-060685
N/A
0DataRank · unranked
7 citations

Matthew P. Kronman, Sushama Kattinakere Sreedhara, Massimiliano Russo, Su Been Lee, Theresa Oduol +2 more

Fast Variational Inference for Bayesian Factor Analysis in Single and Multi-Study Settings

Journal of Computational and Graphical Statistics(2024)10.1080/10618600.2024.2356173
N/A
0DataRank · unranked
7 citations

Alejandra Avalos‐Pacheco, Massimiliano Russo, Roberta De Vito, Blake Hansen

Hierarchical clustering analysis to inform classification of congenital malformations for surveillance of medication safety in pregnancy

American Journal of Epidemiology(2024)10.1093/aje/kwae272
N/A
0DataRank · unranked
2 citations

Shirley Wang, Sonia Hernández–Dı́az, Kathryn J. Gray, Seanna Vine, Massimiliano Russo +5 more