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

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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
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  Data: <searchLink fieldCode="AU" term="%22Burrows+L%22">Burrows L</searchLink>; Department of Mathematical Sciences and Centre for Mathematical Imaging Techniques, University of Liverpool, Liverpool, United Kingdom.<br /><searchLink fieldCode="AU" term="%22Sculthorpe+D%22">Sculthorpe D</searchLink>; Biodiscovery Institute, Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom.<br /><searchLink fieldCode="AU" term="%22Zhang+H%22">Zhang H</searchLink>; Department of Eye and Vision Science, University of Liverpool, Liverpool, United Kingdom.<br /><searchLink fieldCode="AU" term="%22Rehman+O%22">Rehman O</searchLink>; Department of Histopathology, Nottingham University Hospitals NHS, Nottingham, United Kingdom.<br /><searchLink fieldCode="AU" term="%22Mukherjee+A%22">Mukherjee A</searchLink>; Biodiscovery Institute, Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom.; Department of Histopathology, Nottingham University Hospitals NHS, Nottingham, United Kingdom.<br /><searchLink fieldCode="AU" term="%22Chen+K%22">Chen K</searchLink>; 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.
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  Data: <searchLink fieldCode="JN" term="%22101528849%22">Journal of pathology informatics</searchLink> [J Pathol Inform] 2023 Nov 19; Vol. 15, pp. 100351. <i>Date of Electronic Publication: </i>2023 Nov 19 (<i>Print Publication: </i>2024).
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier+Inc%22">Elsevier Inc </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101528849 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Print <i>ISSN: </i>2229-5089 (Print) <i>NLM ISO Abbreviation: </i>J Pathol Inform <i>Subsets: </i>PubMed not MEDLINE
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        Value: 10.1016/j.jpi.2023.100351
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              Text: 2023 Nov 19
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