Author

K. Sirinukunwattana

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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Cancer Biology· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Organism:human· 2 Assay:imaging· 2

Frequent Co-Authors

J. Rittscher· 2 shared A. A. Meade· 1 shared A. Aberdeen· 1 shared A. Blake· 1 shared A. Chatzipli· 1 shared A. D. Beggs· 1 shared A. Mead· 1 shared B. Psaila· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersCancer Biology

J. Rittscher

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2 papers

Recent·Most cited

Cancer BiologyGutPeer-reviewedJul 20, 2020

Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning

K. Sirinukunwattana, E. Domingo, S. Richman…·V. Koelzer

This paper develops imCMS, a deep learning method to classify colorectal cancer subtypes from histological images, showing improved accuracy over bioinformatic methods.

DOI 10.1136/gutjnl-2019-319866

humanimaging

𝕏 PostBluesky

PathologybioRxivPreprintSep 11, 2019

Improving the diagnosis and classification of Ph-negative myeloproliferative neoplasms through deep phenotyping

K. Sirinukunwattana, A. Aberdeen, H. Theissen…·D. Royston

This paper develops a machine-learning approach to automate megakaryocyte morphology analysis in bone marrow trephine samples to improve diagnosis of Ph-negative myeloproliferative neoplasms.

DOI 10.1101/762013

humanimaging

𝕏 PostBluesky