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

Francesco Calivá

ORCID: 0000-0002-0425-7511
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 1%percentile
6.5Author 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.

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

Research at the University of Copenhagen (University of Copenhagen)(2021)10.1148/ryai.2021200078
Top 6%
3.6DataRank
Top 6%78 citations

Francesco Calivá, Claudia Iriondo, Aliasghar Mortazi, Sachin Jambawalikar, Ulaş Bağcı +25 more

Papers

Driven by 9 papers — median percentile 91. Top paper: “The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset”.

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

Research at the University of Copenhagen (University of Copenhagen)(2021)10.1148/ryai.2021200078
Top 6%
3.6DataRank
Top 6%78 citations

Francesco Calivá, Claudia Iriondo, Aliasghar Mortazi, Sachin Jambawalikar, Ulaş Bağcı +25 more

The KNee OsteoArthritis Prediction (KNOAP2020) challenge: An image analysis challenge to predict incident symptomatic radiographic knee osteoarthritis from MRI and X-ray images

Osteoarthritis and Cartilage(2022)10.1016/j.joca.2022.10.001
Top 9%
2.3DataRank
Top 9%60 citations

J. Runhaar, Rianne A. van der Heijden, Maryam Zokaeinikoo, Mingrui Yang, X. Li +27 more

Deep Learning for Hierarchical Severity Staging of Anterior Cruciate Ligament Injuries from MRI

Radiology Artificial Intelligence(2020)10.1148/ryai.2020190207
Top 31%
0.646DataRank
Top 31%73 citations

Io Flament, Bruno A. A. Nunes, Rutwik Shah, Radhika Tibrewala, Francesco Calivá +4 more

Adversarial Robust Training of Deep Learning MRI Reconstruction Models

The Journal of Machine Learning for Biomedical Imaging(2021)10.59275/j.melba.2021-df47
N/A
0DataRank · unranked
6 citations

Kaiyang Cheng, Rutwik Shah, Valentina Pedoia, Francesco Calivá

Uncovering associations between data-driven learned qMRI biomarkers and chronic pain

Scientific Reports(2021)10.1038/s41598-021-01111-x
N/A
0DataRank · unranked
21 citations

Jinhee J. Lee, Francesco Calivá, Claudia Iriondo, Felix Liu, Sharmila Majumdar +2 more

Region of interest-specific loss functions improve T2 quantification with ultrafast T2 mapping MRI sequences in knee, hip and lumbar spine

Scientific Reports(2022)10.1038/s41598-022-26266-z
N/A
0DataRank · unranked
9 citations

Misung Han, Francesco Calivá, Valentina Pedoia, Sharmila Majumdar, Aniket Tolpadi

Large‐Scale Analysis of Meniscus Morphology as Risk Factor for Knee Osteoarthritis

Arthritis & Rheumatology(2023)10.1002/art.42623
N/A
0DataRank · unranked
18 citations

Emily Xie, Vincent Chen, Claudia Iriondo, Francesco Calivá, Richard B. Souza +3 more

The knee connectome: A novel tool for studying spatiotemporal change in cartilage thickness

Journal of Orthopaedic Research®(2023)10.1002/jor.25637
N/A
0DataRank · unranked
2 citations

Kenneth T. Gao, Vincent Chen, Alejandro Morales Martinez, Claudia Iriondo, Francesco Calivá +3 more

Improving the Generalizability of Deep Learning for T2-Lesion Segmentation of Gliomas in the Post-Treatment Setting

Bioengineering(2024)10.3390/bioengineering11050497
N/A
0DataRank · unranked
0 citations

Francesco Calivá, Pablo F. Damasceno, Tracy Luks, Marisa Lafontaine, Julia Cluceru +7 more