Author

James B. Golomb

New York UniversityORCID 0000-0003-0095-8625Unclaimed 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 Assay:imaging· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:spatial domain detection· 1 Approach:statistical model· 1

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AJAX ELIS GEORGEiD· 1 shared Alicia Meng· 1 shared Andrei I. HolodnyiD· 1 shared Benjamin Ades‐AroniD· 1 shared Dmitry S. NovikoviD· 1 shared Els FieremansiD· 1 shared Henry RusinekiD· 1 shared Ileana JelescuiD· 1 shared

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2018-2022 · peak 1/yr

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10 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

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2 papers

Recent·Most cited

BioinformaticsJournal of Imaging Informatics in MedicinePeer-reviewedMay 17, 2022

Deep Learning Achieves Neuroradiologist-Level Performance in Detecting Hydrocephalus Requiring Treatment

Yu Huang, Raquel Moreno, Rachna Malani…·Robert J. Young

The paper develops a deep learning model to detect hydrocephalus requiring treatment from MRI scans, achieving performance comparable to neuroradiologists.

13 citations

humanimaging

𝕏 PostBluesky

NeurosciencebioRxivPreprintOct 13, 2018

Spatial relationships between white matter degeneration, amyloid load and cortical volume in amnestic mild cognitive impairment

Ileana Jelescu, Timothy M. Shepherd, Dmitry S. Novikov…·Els Fieremans

The paper examines spatial relationships between white matter degeneration, amyloid load, and cortical volume in amnestic mild cognitive impairment and finds that WM degeneration correlates more strongly with cortical volume than amyloid.

3 citations

humanimaging

𝕏 PostBluesky