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

Sandra Vieira

ORCID: 0000-0002-2141-1963
NeuroscienceMedicinePsychologyComputer 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 5%percentile
0.390Author 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.

PSYSCAN multi-centre study: baseline characteristics and clinical outcomes of the clinical high risk for psychosis sample

Schizophrenia(2025)10.1038/s41537-025-00598-x
Top 47%
0.390DataRank
Top 47%8 citations

Sandra Vieira, Dominic Oliver, Alexis E. Cullen, Matthew J. Kempton, Paolo Fusar‐Poli +86 more

Papers

Driven by 7 papers — median percentile 53. Top paper: “PSYSCAN multi-centre study: baseline characteristics and clinical outcomes of the clinical high risk for psychosis sample”.

PSYSCAN multi-centre study: baseline characteristics and clinical outcomes of the clinical high risk for psychosis sample

Schizophrenia(2025)10.1038/s41537-025-00598-x
Top 47%
0.390DataRank
Top 47%8 citations

Sandra Vieira, Dominic Oliver, Alexis E. Cullen, Matthew J. Kempton, Paolo Fusar‐Poli +86 more

Normative modelling using deep autoencoders: a multi-cohort study on mild cognitive impairment and Alzheimer’s disease

bioRxiv (Cold Spring Harbor Laboratory)(2020)10.1101/2020.02.10.931824
N/A
0DataRank · unranked
11 citations

Cristina Scarpazza, Rafael Garcia‐Dias, Sandra Vieira, Lea Baecker, Pedro F. da Costa +9 more

Brain age prediction: A comparison between machine learning models using region‐ and voxel‐based morphometric data

Human Brain Mapping(2021)10.1002/hbm.25368
N/A
0DataRank · unranked
117 citations

Jessica Dafflon, Pedro F. da Costa, Rafael Garcia‐Dias, Sandra Vieira, Cristina Scarpazza +5 more

Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners

NeuroImage(2020)10.1016/j.neuroimage.2020.117127
N/A
0DataRank · unranked
90 citations

Cristina Scarpazza, Lea Baecker, Sandra Vieira, Walter Hugo Lopez Pinaya, Aiden Corvin +30 more

Exploring the latent structure of behavior using the Human Connectome Project’s data

Scientific Reports(2023)10.1038/s41598-022-27101-1
N/A
0DataRank · unranked
20 citations

Thomas A. W. Bolton, Jagruti Patel, Anjali Tarun Nahálka, Sandra Vieira, Patric Hagmann +1 more

Neurofind: using deep learning to make individualised inferences in brain-based disorders

Translational Psychiatry(2025)10.1038/s41398-025-03290-x
N/A
0DataRank · unranked
3 citations

Lea Baecker, Walter Hugo Lopez Pinaya, Rafael Garcia‐Dias, Cristina Scarpazza, Vince D. Calhoun +2 more

Using normative modelling to detect disease progression in mild cognitive impairment and Alzheimer’s disease in a cross-sectional multi-cohort study

Scientific Reports(2021)10.1038/s41598-021-95098-0
N/A
0DataRank · unranked
83 citations

Cristina Scarpazza, Rafael Garcia‐Dias, Sandra Vieira, Lea Baecker, Pedro F. da Costa +7 more