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

Nidhi Naik

Icahn School of Medicine at Mount Sinai

ORCID: 0000-0002-3165-4926
MedicineComputer Science

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 2%percentile
2.4Author 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.

Characterization of Patients Who Return to Hospital Following Discharge from Hospitalization For COVID-19

medRxiv(2020)10.1101/2020.05.17.20104604
Top 9%
2.4DataRank
Top 9%34 citations

Felix Richter, Valentı́n Fuster, Jessica De Freitas, Nidhi Naik, Keith Sigel +10 more

Papers

Driven by 7 papers — median percentile 91. Top paper: “Characterization of Patients Who Return to Hospital Following Discharge from Hospitalization For COVID-19”.

Characterization of Patients Who Return to Hospital Following Discharge from Hospitalization For COVID-19

medRxiv(2020)10.1101/2020.05.17.20104604
Top 9%
2.4DataRank
Top 9%34 citations

Felix Richter, Valentı́n Fuster, Jessica De Freitas, Nidhi Naik, Keith Sigel +10 more

Characterization of Patients Who Return to Hospital Following Discharge from Hospitalization for COVID-19

Journal of General Internal Medicine(2020)10.1007/s11606-020-06120-6
N/A
0.712DataRank · unranked
114 citations

Felix Richter, Valentı́n Fuster, Jessica K. De Freitas, Nidhi Naik, Keith Sigel +10 more

Contrastive learning improves critical event prediction in COVID-19 patients

Patterns(2021)10.1016/j.patter.2021.100389
N/A
0.292DataRank · unranked
6 citations

Hossein Honarvar, Suraj K. Jaladanki, Chengxi Zang, Nidhi Naik, Sulaiman Somani +13 more

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation

Journal of Medical Internet Research(2020)10.2196/24018
N/A
0DataRank · unranked
240 citations

Sulaiman Somani, Adam Russak, Jessica K. De Freitas, Fayzan Chaudhry, Ishan Paranjpe +43 more

Real World Evidence and Clinical Utility of KidneyIntelX on Patients With Early-Stage Diabetic Kidney Disease: Interim Results on Decision Impact and Outcomes

Journal of Primary Care & Community Health(2022)10.1177/21501319221138196
N/A
0DataRank · unranked
6 citations

Aida Vega, Catherine Sinfield, Nidhi Naik, Shivani Rathi, Sharlene Martin +9 more

The emerging role of growth differentiation factor 15 as a potential disease biomarker in juvenile dermatomyositis

Lara D. Veeken(2023)10.1093/rheumatology/kead654
N/A
0DataRank · unranked
11 citations

Jorge A. González-Chapa, Lauren M. Pachman, Gabrielle Morgan, Nidhi Naik, Susan Shenoi +2 more

A Real-World Precision Medicine Program Including the KidneyIntelX Test Effectively Changes Management Decisions and Outcomes for Patients With Early-Stage Diabetic Kidney Disease

Journal of Primary Care & Community Health(2024)10.1177/21501319231223437
N/A
0DataRank · unranked
10 citations

David W. Lam, Aida Vega, Stephanie Wang, Leonard Amoruso, T Müller +15 more