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Mathematical modelling and deep learning algorithms to automate assessment of single and digitally multiplexed immunohistochemical stains in tumoural stroma.

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Bibliographic Details
Title: Mathematical modelling and deep learning algorithms to automate assessment of single and digitally multiplexed immunohistochemical stains in tumoural stroma.
Authors: Burrows L; Department of Mathematical Sciences and Centre for Mathematical Imaging Techniques, University of Liverpool, Liverpool, United Kingdom., Sculthorpe D; Biodiscovery Institute, Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom., Zhang H; Department of Eye and Vision Science, University of Liverpool, Liverpool, United Kingdom., Rehman O; Department of Histopathology, Nottingham University Hospitals NHS, Nottingham, United Kingdom., Mukherjee A; Biodiscovery Institute, Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom.; Department of Histopathology, Nottingham University Hospitals NHS, Nottingham, United Kingdom., Chen K; Department of Mathematical Sciences and Centre for Mathematical Imaging Techniques, University of Liverpool, Liverpool, United Kingdom.; Department of Mathematics and Statistics, University of Strathclyde, Glasgow, United Kingdom.
Source: Journal of pathology informatics [J Pathol Inform] 2023 Nov 19; Vol. 15, pp. 100351. Date of Electronic Publication: 2023 Nov 19 (Print Publication: 2024).
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Inc Country of Publication: United States NLM ID: 101528849 Publication Model: eCollection Cited Medium: Print ISSN: 2229-5089 (Print) NLM ISO Abbreviation: J Pathol Inform Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2229-5089
DOI:10.1016/j.jpi.2023.100351