Author

Jared Dunnmon

Stanford UniversityORCID 0000-0002-4002-0562Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:GWAS / association mapping· 1 Assay:GWAS summary statistics· 1 Assay:imaging· 1 Approach:statistical model· 1

Frequent Co-Authors

Christopher RéiD· 2 shared James Rush PriestiD· 2 shared Aldo Córdova‐PalomeraiD· 1 shared Euan Angus AshleyiD· 1 shared Fred G. Sala· 1 shared Heliodoro TejedaiD· 1 shared Henry ChubbiD· 1 shared Jason FriesiD· 1 shared

Activity by Year

2019-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersBioinformatics

Christopher RéORCID

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2 papers

Recent·Most cited

Mendelian Randomization with Instrumental Variable Synthesis (IVY)

Zhaobin Kuang, Aldo Córdova‐Palomera, Fred G. Sala, Sen Wu, Jared Dunnmon, Chris Ré, James Rush Priest

This paper introduces IVY, a method that improves Mendelian Randomization by combining genetic variants using probabilistic models, showing better results than allele scoring at moderate sample sizes.

bioRxiv · Sep 9, 2019 · PreprintBioinformatics

Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences

Jason Fries, Paroma Varma, Vincent S. Chen, Ke Xiao, Heliodoro Tejeda, Priyanka Saha, Jared Dunnmon, Henry Chubb, Shiraz Arif Maskatia, Madalina Fiterau, Scott L. Delp, Euan Angus Ashley, Christopher Ré, James Rush Priest

This paper develops a weakly supervised deep learning model to classify aortic valve malformations using unlabeled cardiac MRI sequences, showing improved performance over supervised models.

Nature Communications · Jul 15, 2019Peer-reviewedBioinformatics