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

Martin Vallières

Université de Sherbrooke

ORCID: 0000-0001-7639-8172

Also affiliated with McGill University Health Centre, McGill University

MedicineComputer ScienceEngineering

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
0.524Author 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.

Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data

Korean Journal of Radiology(2021)10.3348/kjr.2020.1104
Top 37%
0.524DataRank
Top 37%32 citations

Yanhe Xiao, Zhicheng Jiao, Rujapa Thepumnoeysuk, Kasey Halsey, Jing Wu +17 more

Papers

Driven by 6 papers — median percentile 63. Top paper: “METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII”.

METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII

Insights into Imaging(2024)10.1186/s13244-023-01572-w
N/A
5.8DataRank · unranked
279 citations

Tugba Akinci D’Antonoli, Nathaniel D. Mercaldo, Ángel Alberich‐Bayarri, Bettina Baeßler, Ilaria Ambrosini +55 more

The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

Radiology(2020)10.1148/radiol.2020191145
N/A
1.2DataRank · unranked
3976 citations

Martin Vallières, Mahmoud A. Abdalah, Hugo J.W.L. Aerts, Vincent Andrearczyk, Aditya Apte +58 more

Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data

Korean Journal of Radiology(2021)10.3348/kjr.2020.1104
Top 37%
0.524DataRank
Top 37%32 citations

Yanhe Xiao, Zhicheng Jiao, Rujapa Thepumnoeysuk, Kasey Halsey, Jing Wu +17 more

Deep Learning to Distinguish Benign from Malignant Renal Lesions Based on Routine MR Imaging

Clinical Cancer Research(2020)10.1158/1078-0432.ccr-19-0374
N/A
0DataRank · unranked
146 citations

Yijun Zhao, Robin Wang, Marcello Chang, Subhanik Purkayastha, Ken Chang +13 more

Radiomics-Based Machine Learning for Outcome Prediction in a Multicenter Phase II Study of Programmed Death-Ligand 1 Inhibition Immunotherapy for Glioblastoma

American Journal of Neuroradiology(2022)10.3174/ajnr.a7488
N/A
0DataRank · unranked
36 citations

Elizabeth Flagg, Ken Chang, Harrison X. Bai, Hugo J.W.L. Aerts, Martin Vallières +3 more

Unraveling Radiomics Complexity: Strategies for Optimal Simplicity in Predictive Modeling

arXiv (Cornell University)(2024)10.48550/arxiv.2407.04888
N/A
0DataRank · unranked
0 citations

Teodora Boblea Podasca, Alex Zwanenburg, Taman Upadhaya, Jorge Barrios, David R. Raleigh +16 more