Author

Livia Faes

Moorfields Eye Hospital NHS Foundation TrustORCID 0000-0002-4159-3960Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

Alastair Keith DennistoniD· 1 shared Christoph KerniD· 1 shared Dawn A. SimiD· 1 shared Dun Jack FuiD· 1 shared Edward KorotiD· 1 shared Gabriella MoraesiD· 1 shared Joseph R. Ledsam· 1 shared Konstantinos BalaskasiD· 1 shared

Activity by Year

2019-2019 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Alastair Keith DennistonORCID

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1 paper

Recent·Most cited

Feasibility of Automated Deep Learning Design for Medical Image Classification by Healthcare Professionals with Limited Coding Experience

Livia Faes, Siegfried K. Wagner, Dun Jack Fu, Xiaoxuan Liu, Edward Korot, Joseph R. Ledsam, Trevor Back, Reena Chopra, Nikolas Pontikos, Christoph Kern, Gabriella Moraes, Martin K. Schmid, Dawn A. Sim, Konstantinos Balaskas, Lucas M. Bachmann, , Pearse Andrew Keane

This study evaluates automated deep learning tools for medical image classification by non-experts, showing high performance in some tasks but limitations in external validation and dataset quality.

bioRxiv · May 27, 2019 · PreprintBioinformatics