Author

John S. Shawe-Taylor

University College LondonORCID 0000-0002-2030-0073Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

André AltmanniD· 1 shared Andreas Jochen FallgatteriD· 1 shared Daan ChristiaensiD· 1 shared Jacques‐Donald TournieriD· 1 shared Janaı́na Mourão-MirandaiD· 1 shared Jessica SchrouffiD· 1 shared João M. MonteiroiD· 1 shared Massimiliano PontiliD· 1 shared

Activity by Year

2018-2019 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperNeuroscience

André AltmannORCID

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2 papers

Recent·Most cited

Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important

Michele Donini, João M. Monteiro, Massimiliano Pontil, Tim Hahn, Andreas Jochen Fallgatter, John S. Shawe-Taylor, Janaı́na Mourão-Miranda

The paper proposes a framework combining neuroimaging and clinical data for mental health diagnosis using EasyMKL and feature selection, showing improved performance over baseline methods.

NeuroImage · Mar 17, 2019Peer-reviewedNeuroscience

Grey matter biomarker identification in Schizophrenia: detecting regional alterations and their underlying substrates

Vasiliki Chatzi, Rui Pedro A. G. Teixeira, John S. Shawe-Taylor, André Altmann, Owen O’Daly, Daan Christiaens, Jessica Schrouff, Jacques‐Donald Tournier

This paper develops a machine learning framework to identify sparse grey matter biomarkers in Schizophrenia and their biological substrates using structural MRI data.

bioRxiv · Jun 28, 2018 · PreprintNeuroscience