Author

D. Saeed-Vafa

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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Cancer Biology· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Assay:imaging· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Organism:human· 1

Frequent Co-Authors

A. Hakam· 1 shared A. Lopez· 1 shared A. M. Magliocco· 1 shared B. M. Reid· 1 shared D. C. Marchion· 1 shared D. Linsley· 1 shared D.-T. Chen· 1 shared F. Khalil· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperCancer Biology

A. Hakam

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2 papers

Recent·Most cited

Deceptive learning in histopathology

S. Shahamatdar, D. Saeed-Vafa, D. Linsley, F. Khalil, K. L. Lovinger, L. Li, H. L. McLeod, S. Ramachandran, T. Serre

This paper analyzes whether deep learning models in histopathology learn trustworthy or deceptive strategies, finding that some recent advances in molecular profiling from H&E slides are unreliable.

bioRxiv · Apr 21, 2022Pathology

Utilizing Digital Pathology to Quantify Stromal Caveolin-1 Expression in Malignant and Benign Ovarian Tumors: Associations with Clinicopathological Parameters and Clinical Outcomes

D. Saeed-Vafa, D. C. Marchion, S. M. McCarthy, A. Hakam, A. Lopez, R. M. Wenham, S. M. Apte, D.-T. Chen, A. M. Magliocco, J. M. Lancaster, B. M. Reid, J. B. Permuth

This study quantifies stromal caveolin-1 expression in ovarian tumors using IHC and IF, finding downregulation in cancer stroma but no correlation with clinical outcomes.

bioRxiv · Aug 18, 2021Cancer Biology