Author

N. Razavian

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 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Approach:deep learning· 3 Research Focus:differential expression· 3 Assay:imaging· 3 Assay:fluorescence / live-cell microscopy· 2 Organism:human· 2 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1

Frequent Co-Authors

A. Tsirigos· 3 shared N. Coudray· 3 shared D. Fenyo· 2 shared T. Sakellaropoulos· 2 shared A. Hatzimemos· 1 shared A. L. Moreira· 1 shared D. Donnelly· 1 shared E. Esteva· 1 shared

Activity by Year

2017-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 34 mutual co-author links

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3 shared papersPathology

A. Tsirigos

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

A Deep Learning Approach for Rapid Mutational Screening in Melanoma

R. Kim, S. Nomikou, N. Coudray, G. Jour, Z. Dawood, R. Hong, E. Esteva, T. Sakellaropoulos, D. Donnelly, U. Moran, A. Hatzimemos, J. S. Weber, N. Razavian, I. Aifantis, D. Fenyo, , A. Tsirigos

This paper develops a deep learning model to detect BRAF mutations in melanoma histopathology images using whole slide images from 256 patients, achieving AUC scores of 0.96 and 0.72.

bioRxiv · Aug 19, 2020 · PreprintPathology

Efficient pan-cancer whole-slide image classification and outlier detection using convolutional neural networks

S. Bilaloglu, J. Wu, E. Fierro, R. D. Sanchez, P. S. Ocampo, N. Razavian, N. Coudray, A. Tsirigos

This paper introduces a simplified CNN architecture for efficient pan-cancer whole-slide image classification and outlier detection.

bioRxiv · May 14, 2019 · PreprintPathology

Classification and Mutation Prediction from Non-Small Cell Lung Cancer Histopathology Images using Deep Learning

N. Coudray, A. L. Moreira, T. Sakellaropoulos, D. Fenyo, N. Razavian, A. Tsirigos

This study uses deep learning to classify lung cancer subtypes and predict gene mutations from histopathology images, achieving high accuracy and outperforming human pathologists.

bioRxiv · Oct 3, 2017Cancer Biology