Author

E. J. Burks

Primary ORCID profile (0000-0002-3122-2875 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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E. J. BurksiD1 paper · Boston University

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:fluorescence / live-cell microscopy· 1 Approach:graph neural network· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

D. T. Merrick· 1 shared E. J. Green· 1 shared J. E. Beane· 1 shared M. E. Reid· 1 shared R. H. Gindra· 1 shared S. A. Mazzilli· 1 shared V. B. Kolachalama· 1 shared Y. Zheng· 1 shared

Activity by Year

2023-2023 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperPathology

D. T. Merrick

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1 paper

Recent·Most cited

Graph perceiver network for lung tumor and bronchial premalignant lesion stratification from histopathology

R. H. Gindra, Y. Zheng, E. J. Green, M. E. Reid, S. A. Mazzilli, D. T. Merrick, E. J. Burks, V. B. Kolachalama, J. E. Beane

This paper introduces GRAPE-Net, a graph-based model that stratifies bronchial premalignant lesions using histopathology images, showing improved classification accuracy for lung cancer subtypes.

bioRxiv · Oct 16, 2023Pathology