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Artificial intelligence-based morphological fingerprinting of megakaryocytes: a new tool for assessing disease in MPN patients

Abstract:

Accurate diagnosis and classification of myeloproliferative neoplasms (MPNs) requires integration of clinical, morphological, and genetic findings. Despite major advances in our understanding of the molecular and genetic basis of MPNs, the morphological assessment of bone marrow trephines (BMT) is critical in differentiating MPN subtypes and their reactive mimics. However, morphological assessment is heavily constrained by a reliance on subjective, qualitative, and poorly reproducible criteri...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1182/bloodadvances.2020002230

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Division:
MSD
Department:
NDM
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Institute of Biomedical Engineering
Role:
Author
ORCID:
0000-0002-4628-9722
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Institution:
University of Oxford
Division:
MSD
Department:
RDM
Sub department:
RDM Clinical Laboratory Sciences
Role:
Author
ORCID:
0000-0002-9100-2954
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
RDM
Sub department:
Weatherall Insti. of Molecular Medicine
Role:
Author
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Wellcome Trust More from this funder
Publisher:
American Society of Hematology Publisher's website
Journal:
Blood Advances Journal website
Volume:
4
Issue:
14
Pages:
3284-3294
Publication date:
2020-07-24
Acceptance date:
2020-06-15
DOI:
EISSN:
2473-9537
ISSN:
2473-9529
Pmid:
32706893
Language:
English
Keywords:
Pubs id:
1123877
Local pid:
pubs:1123877
Deposit date:
2020-09-22

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