Author

Louise Jane Michaelis

Newcastle upon Tyne Hospitals NHS Foundation TrustORCID 0000-0001-8229-154XUnclaimed 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:clustering· 1 Approach:deep learning· 1 Organism:human· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Andrew Fuller· 1 shared Andrew J. FilbyiD· 1 shared Carly Knill· 1 shared Daniel PeraltaiD· 1 shared Emma Ladlow· 1 shared Maxim LippeveldiD· 1 shared Yvan SaeysiD· 1 shared

Activity by Year

2019-2019 · peak 1/yr

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7 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

Andrew Fuller

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1 paper

Recent·Most cited

BioinformaticsCytometry Part APeer-reviewedNov 5, 2019

Classification of human white blood cells using machine learning for stain-free imaging flow cytometry

Maxim Lippeveld, Carly Knill, Emma Ladlow…·Daniel Peralta

This study compares classical machine learning and deep learning for classifying white blood cells using stain-free imaging flow cytometry, achieving balanced accuracies of 0.776 and 0.697 for white blood cells and 0.866 and 0.867 for eosinophils.

117 citationstop 3%

humanimaging

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