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

Cem M. Deniz

NYU Langone Health

ORCID: 0000-0001-8809-5945

Also affiliated with Hinge Health, New York University

MedicineEngineering

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
7.6Author DataRank

Indexed papers

4in 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 4 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 11 papers — median percentile 88. 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

Three-dimensional MRI Bone Models of the Glenohumeral Joint Using Deep Learning: Evaluation of Normal Anatomy and Glenoid Bone Loss

Radiology Artificial Intelligence(2020)10.1148/ryai.2020190116
Top 15%
1.4DataRank
Top 15%33 citations

Cem M. Deniz, Erin F. Alaia, Natalia Gorelik, James S. Babb, Jared Dublin +2 more

Towards automatic cartilage quantification in clinical trials – Continuing from the 2019 IWOAI knee segmentation challenge

Osteoarthritis Imaging(2023)10.1016/j.ostima.2023.100087
Top 48%
0.370DataRank
Top 48%7 citations

Arjun Desai, Cem M. Deniz, Haresh Rengaraj Rajamohan, Ravinder R. Regatte, Claudia Iriondo +17 more

The impact of data augmentation and transfer learning on the performance of deep learning models for the segmentation of the hip on 3D magnetic resonance images

Informatics in Medicine Unlocked(2024)10.1016/j.imu.2023.101444
N/A
0DataRank · unranked
14 citations

Cem M. Deniz, Richard Kijowski, Thomas Youm, Riccardo Lattanzi, Eros Montin

Estimation of time-to-total knee replacement surgery with multimodal modeling and artificial intelligence

Computers in Biology and Medicine(2025)10.1016/j.compbiomed.2025.110364
N/A
0DataRank · unranked
2 citations

Eisa Hedayati, Haresh Rengaraj Rajamohan, Kyunghyun Cho, Gregory Chang, Richard Kijowski +2 more

Prediction of Total Knee Replacement and Diagnosis of Osteoarthritis by Using Deep Learning on Knee Radiographs: Data from the Osteoarthritis Initiative

Radiology(2020)10.1148/radiol.2020192091
N/A
0DataRank · unranked
237 citations

Bofei Zhang, Jimin Tan, Yiqiu Shen, Krzysztof J. Geras, James S. Babb +4 more

MR-Transformer: A Vision Transformer-based Deep Learning Model for Total Knee Replacement Prediction Using MRI

Radiology Artificial Intelligence(2025)10.1148/ryai.240373
N/A
0DataRank · unranked
2 citations

Shengjia Chen, Çiğdem Özkan, Haresh Rengaraj Rajamohan, Kyunghyun Cho, Richard Kijowski +2 more

Estimating time-to-total knee replacement on radiographs and MRI: a multimodal approach using self-supervised deep learning

Radiology Advances(2022)10.1093/radadv/umae030
N/A
0DataRank · unranked
2 citations

Shengjia Chen, Chaojie Zhang, Kyunghyun Cho, Richard Kijowski, Cem M. Deniz +1 more

Prediction of total knee replacement using deep learning analysis of knee MRI

Scientific Reports(2023)10.1038/s41598-023-33934-1
N/A
0DataRank · unranked
41 citations

Tianyu Wang, Kevin Leung, Gregory Chang, Kyunghyun Cho, Richard Kijowski +2 more

Artificial intelligence in knee osteoarthritis: A comprehensive review for 2022

Osteoarthritis Imaging(2023)10.1016/j.ostima.2023.100161
N/A
0DataRank · unranked
31 citations

Cem M. Deniz, Çiğdem Özkan