Author

Aditya Khosla

PathAI (United States)

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· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Organism:human· 2 Assay:imaging· 2 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Abhik Lahiri· 1 shared Amaro N Taylor-WeineriD· 1 shared Andrew H. BeckiD· 1 shared Aude OlivaiD· 1 shared Benjamin GlassiD· 1 shared Chirag Maheshwari· 1 shared Dimitrios PantazisiD· 1 shared Hunter L. Elliott· 1 shared

Activity by Year

2015-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBioinformatics

Abhik Lahiri

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Dense, high-resolution mapping of cells and tissues from pathology images for the interpretable prediction of molecular phenotypes in cancer

James A. Diao, Wan Fung Chui, Jason K. Wang, Richard N. Mitchell, Sudha K. Rao, Murray B. Resnick, Abhik Lahiri, Chirag Maheshwari, Benjamin Glass, Victoria Mountain, Jennifer K. Kerner, Michael Montalto, Aditya Khosla, Ilan N. Wapinski, Andrew H. Beck, , Hunter L. Elliott

This paper develops a method to predict molecular phenotypes from cancer pathology images using interpretable features, showing correlations with tumor microenvironment markers and predictive power for molecular signatures.

bioRxiv · Aug 2, 2020 · PreprintBioinformatics

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks

Radoslaw Martin Cichy, Aditya Khosla, Dimitrios Pantazis, Aude Oliva

This study uses MEG and deep neural networks to show that spatial layout processing in scene recognition occurs around 250ms and is captured by a deep neural network model.

bioRxiv · Nov 23, 2015Neuroscience