Author

Sameer H. Halani

Emory University

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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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Daniel Jay BratiD· 2 shared David A. GutmaniD· 2 shared Jose Enrique Velazquez Vega· 2 shared Lee CooperiD· 2 shared Mohamed T. AmgadiD· 2 shared Chengliang Dong· 1 shared Congzheng SongiD· 1 shared Fatemeh AmrollahiiD· 1 shared

Activity by Year

2017-2017 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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2 shared papersBioinformatics

Daniel Jay BratORCID

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2 papers

Recent·Most cited

Interactive Phenotyping Of Large-Scale Histology Imaging Data With HistomicsML

Michael Nalisnik, Mohamed T. Amgad, Sanghoon Lee, Sameer H. Halani, Jose Enrique Velazquez Vega, Daniel Jay Brat, David A. Gutman, Lee Cooper

HistomicsML enables interactive machine learning for analyzing histology images to identify phenotypes and predict survival in gliomas.

Scientific Reports · Oct 31, 2017Peer-reviewedBioinformatics

Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models

Safoora Yousefi, Fatemeh Amrollahi, Mohamed T. Amgad, Chengliang Dong, Joshua E. Lewis, Congzheng Song, David A. Gutman, Sameer H. Halani, Jose Enrique Velazquez Vega, Daniel Jay Brat, Lee Cooper

This paper applies deep learning and Bayesian optimization to predict cancer clinical outcomes from genomic data, showing improved prognostic accuracy through transfer learning and providing an open-source framework.

Scientific Reports · Sep 11, 2017Peer-reviewedBioinformatics