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Precision immunoprofiling by image analysis and artificial intelligence

Abstract:

Clinical success of immunotherapy is driving the need for new prognostic and predictive assays to inform patient selection and stratification. This requirement can be met by a combination of computational pathology and artificial intelligence. Here, we critically assess computational approaches supporting the development of a standardized methodology in the assessment of immune-oncology biomarkers, such as PD-L1 and immune cell infiltrates. We examine immunoprofiling through spatial analysis ...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1007/s00428-018-2485-z

Authors


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Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
Oncology
Role:
Author
ORCID:
0000-0001-9206-4885
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Subgroup:
Oxford Ludwig Institute
Role:
Author
Publisher:
Springer Berlin Heidelberg Publisher's website
Journal:
Virchows Archiv Journal website
Volume:
474
Issue:
4
Pages:
511–522
Publication date:
2018-11-23
Acceptance date:
2018-11-09
DOI:
EISSN:
1432-2307
ISSN:
0945-6317
Pubs id:
pubs:946564
URN:
uri:77ba0645-96e5-4bb4-8a6c-3e121fcfc43d
UUID:
uuid:77ba0645-96e5-4bb4-8a6c-3e121fcfc43d
Local pid:
pubs:946564

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