Author

M. I. Jaber

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Pathology· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

C. W. Szeto· 2 shared L. Beziaeva· 2 shared B. Song· 1 shared P. Soon-Shiong· 1 shared P. Spilman· 1 shared P. Yang· 1 shared S. C. Benz· 1 shared

Activity by Year

2021-2021 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 17 mutual co-author links

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2 shared papersPathology

C. W. Szeto

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Author profile →

2 papers

Recent·Most cited

A deep learning-based iterative digital pathology annotation tool

M. I. Jaber, B. Song, L. Beziaeva, C. W. Szeto, P. Spilman, P. Yang, P. Soon-Shiong

This paper introduces a deep learning-based tool for digital pathology annotation that reduces annotation time while maintaining accuracy, validated on CAMELYON16 and TCGA datasets.

bioRxiv · Aug 23, 2021 · PreprintPathology

Deep learning-based risk stratification for HER2-negative breast cancer patients

M. I. Jaber, L. Beziaeva, C. W. Szeto, S. C. Benz

The paper uses deep learning to analyze digital pathology images and clinicopathological data to improve risk stratification for HER2-negative breast cancer patients.

bioRxiv · May 26, 2021 · PreprintPathology