Author

K.G. Phillips

Eli Lilly (United States)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Neuroscience· 1

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Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1 Approach:machine learning (classical)· 1 Organism:rat· 1

Frequent Co-Authors

André MourauxiD· 1 shared Andrea TruiniiD· 1 shared Anna C. SalesiD· 1 shared Anthony Edward PickeringiD· 1 shared Anthony James BlockeeliD· 1 shared James DunhamiD· 1 shared John R. HuxteriD· 1 shared Robert AR DrakeiD· 1 shared

Activity by Year

2021-2021 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 36 mutual co-author links

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1 shared paperNeuroscience

André MourauxORCID

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1 paper

Recent·Most cited

Trial by trial, machine learning approach identifies temporally discrete Aδ- and C-fibre mediated laser evoked potentials that predict pain behaviour in rats.

Anna C. Sales, Anthony James Blockeel, John R. Huxter, James Dunham, Robert AR Drake, Andrea Truini, André Mouraux, Rolf‐Detlef Treede, K.G. Phillips, Anthony Edward Pickering

The paper uses machine learning to analyze single-trial laser evoked potentials (LEPs) in rats, identifying distinct Aδ- and C-fibre mediated responses that predict pain behavior.

bioRxiv · Aug 10, 2021 · PreprintNeuroscience