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

Thiago Gonçalves dos Santos Martins

Ludwig-Maximilians-Universität München

ORCID: 0000-0002-3878-8564
Medicine

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

3in 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 3 indexed papers 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.

Self-supervised retinal thickness prediction enables deep learning from unlabeled data to boost classification of diabetic retinopathy

Zenodo (CERN European Organization for Nuclear Research)(2020)10.5281/zenodo.3625995
Top 100%
0DataRank
Top 100%0 citations

Niklas D. Köhler, Thiago Gonçalves dos Santos Martins, Jakob Siedlecki, Tina Herold, Leonie Keidel +6 more

Papers

Driven by 5 papers — median percentile 0. Top paper: “Self-supervised retinal thickness prediction enables deep learning from unlabelled data to boost classification of diabetic retinopathy”.

Self-supervised retinal thickness prediction enables deep learning from unlabelled data to boost classification of diabetic retinopathy

Nature Machine Intelligence(2020)10.1038/s42256-020-00247-1
N/A
0.650DataRank · unranked
75 citations

Niklas D. Köhler, Jakob Siedlecki, Tina Herold, Leonie Keidel, Ben Asani +6 more

Self-supervised retinal thickness prediction enables deep learning from unlabeled data to boost classification of diabetic retinopathy

bioRxiv (Cold Spring Harbor Laboratory)(2019)10.1101/861757
N/A
0.165DataRank · unranked
2 citations

Niklas D. Köhler, Thiago Gonçalves dos Santos Martins, Jakob Siedlecki, Tina Herold, Leonie Keidel +6 more

Self-supervised retinal thickness prediction enables deep learning from unlabeled data to boost classification of diabetic retinopathy

Zenodo (CERN European Organization for Nuclear Research)(2020)10.5281/zenodo.3625995
Top 100%
0DataRank
Top 100%0 citations

Niklas D. Köhler, Thiago Gonçalves dos Santos Martins, Jakob Siedlecki, Tina Herold, Leonie Keidel +6 more

Self-supervised retinal thickness prediction enables deep learning from unlabeled data to boost classification of diabetic retinopathy

Zenodo (CERN European Organization for Nuclear Research)(2020)10.5281/zenodo.3626854
Top 100%
0DataRank
Top 100%0 citations

Niklas D. Köhler, Thiago Gonçalves dos Santos Martins, Jakob Siedlecki, Tina Herold, Leonie Keidel +6 more

Self-supervised retinal thickness prediction enables deep learning from unlabeled data to boost classification of diabetic retinopathy

Zenodo (CERN European Organization for Nuclear Research)(2020)10.5281/zenodo.3626020
Top 100%
0DataRank
Top 100%0 citations

Niklas D. Köhler, Thiago Gonçalves dos Santos Martins, Jakob Siedlecki, Tina Herold, Leonie Keidel +6 more