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

Jared Dunnmon

Stanford University

ORCID: 0000-0002-4002-0562
MedicineComputer ScienceNeuroscience

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 4%percentile
0.884Author 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.

Comparison of segmentation-free and segmentation-dependent computer-aided diagnosis of breast masses on a public mammography dataset

Journal of Biomedical Informatics(2020)10.1016/j.jbi.2020.103656
Top 23%
0.884DataRank
Top 23%19 citations

Jared Dunnmon, Ann He, Siyi Tang, Christopher Ré, Daniel L. Rubin +1 more

Papers

Driven by 7 papers — median percentile 77. Top paper: “Comparison of segmentation-free and segmentation-dependent computer-aided diagnosis of breast masses on a public mammography dataset”.

Comparison of segmentation-free and segmentation-dependent computer-aided diagnosis of breast masses on a public mammography dataset

Journal of Biomedical Informatics(2020)10.1016/j.jbi.2020.103656
Top 23%
0.884DataRank
Top 23%19 citations

Jared Dunnmon, Ann He, Siyi Tang, Christopher Ré, Daniel L. Rubin +1 more

Impact of Upstream Medical Image Processing on Downstream Performance of a Head CT Triage Neural Network

Radiology Artificial Intelligence(2021)10.1148/ryai.2021200229
N/A
0.425DataRank · unranked
16 citations

Jared Dunnmon, Matthew P. Lungren, Domenico Mastrodicasa, Daniel L. Rubin, Christopher Ré +3 more

PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging

npj Digital Medicine(2020)10.1038/s41746-020-0266-y
N/A
0DataRank · unranked
183 citations

Tanay Kothari, Imon Banerjee, Chris Chute, Robyn L. Ball, Norah Borus +12 more

Hidden stratification causes clinically meaningful failures in machine learning for medical imaging

PubMed(2020)10.1145/3368555.3384468
N/A
0DataRank · unranked
30 citations

Jared Dunnmon, Gustavo Carneiro, Christopher Ré, Luke Oakden‐Rayner

Multi-task weak supervision enables anatomically-resolved abnormality detection in whole-body FDG-PET/CT

Nature Communications(2021)10.1038/s41467-021-22018-1
N/A
0DataRank · unranked
40 citations

Geoffrey Angus, Bhavik N. Patel, Anuj Pareek, Guido Davidzon, Long Jin +3 more

Cross-Modal Data Programming Enables Rapid Medical Machine Learning

Patterns(2020)10.1016/j.patter.2020.100019
N/A
0DataRank · unranked
10 citations

Alexander Ratner, Khaled Saab, Nishith Khandwala, Matthew Markert, Hersh Sagreiya +6 more

Weak supervision as an efficient approach for automated seizure detection in electroencephalography

npj Digital Medicine(2020)10.1038/s41746-020-0264-0
N/A
0DataRank · unranked
102 citations

Jared Dunnmon, Christopher Ré, Daniel L. Rubin, Christopher Lee‐Messer, Khaled Saab