A novel pipeline employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy.
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| Title: | A novel pipeline employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy. |
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| Authors: | Mamalakis M; School of Electrical and Electronic Engineering, University of Sheffield, Sheffield, UK; Insigneo Institute for in-silico, Medicine, University of Sheffield, Sheffield, UK; Department of Infection, Immunity and Cardiovascular Disease, and Department of Computer science, Sheffield, UK; Department of Psychiatry, Cambridge University, Cambridge, UK. Electronic address: co4mma@sheffield.ac.uk., Macfarlane SC; Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, UK., Notley SV; Insigneo Institute for in-silico, Medicine, University of Sheffield, Sheffield, UK; Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK., Gad AKB; Insigneo Institute for in-silico, Medicine, University of Sheffield, Sheffield, UK; Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, UK; Madeira Chemistry Research Centre, University of Madeira, Funchal, Portugal; Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden., Panoutsos G; School of Electrical and Electronic Engineering, University of Sheffield, Sheffield, UK; Insigneo Institute for in-silico, Medicine, University of Sheffield, Sheffield, UK; Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, UK. Electronic address: g.panoutsos@sheffield.ac.uk. |
| Source: | Computers in biology and medicine [Comput Biol Med] 2024 Oct; Vol. 181, pp. 109052. Date of Electronic Publication: 2024 Aug 30. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Elsevier Country of Publication: United States NLM ID: 1250250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0534 (Electronic) Linking ISSN: 00104825 NLM ISO Abbreviation: Comput Biol Med Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 39216406 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A novel pipeline employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Mamalakis+M%22">Mamalakis M</searchLink>; School of Electrical and Electronic Engineering, University of Sheffield, Sheffield, UK; Insigneo Institute for in-silico, Medicine, University of Sheffield, Sheffield, UK; Department of Infection, Immunity and Cardiovascular Disease, and Department of Computer science, Sheffield, UK; Department of Psychiatry, Cambridge University, Cambridge, UK. Electronic address: co4mma@sheffield.ac.uk.<br /><searchLink fieldCode="AU" term="%22Macfarlane+SC%22">Macfarlane SC</searchLink>; Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, UK.<br /><searchLink fieldCode="AU" term="%22Notley+SV%22">Notley SV</searchLink>; Insigneo Institute for in-silico, Medicine, University of Sheffield, Sheffield, UK; Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK.<br /><searchLink fieldCode="AU" term="%22Gad+AKB%22">Gad AKB</searchLink>; Insigneo Institute for in-silico, Medicine, University of Sheffield, Sheffield, UK; Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, UK; Madeira Chemistry Research Centre, University of Madeira, Funchal, Portugal; Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.<br /><searchLink fieldCode="AU" term="%22Panoutsos+G%22">Panoutsos G</searchLink>; School of Electrical and Electronic Engineering, University of Sheffield, Sheffield, UK; Insigneo Institute for in-silico, Medicine, University of Sheffield, Sheffield, UK; Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, UK. Electronic address: g.panoutsos@sheffield.ac.uk. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%221250250%22">Computers in biology and medicine</searchLink> [Comput Biol Med] 2024 Oct; Vol. 181, pp. 109052. <i>Date of Electronic Publication: </i>2024 Aug 30. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article; Research Support, Non-U.S. Gov't – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier%22">Elsevier </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>1250250 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1879-0534 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200104825%22">00104825 </searchLink><i>NLM ISO Abbreviation: </i>Comput Biol Med <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=39216406 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.compbiomed.2024.109052 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 109052 Titles: – TitleFull: A novel pipeline employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mamalakis M – PersonEntity: Name: NameFull: Macfarlane SC – PersonEntity: Name: NameFull: Notley SV – PersonEntity: Name: NameFull: Gad AKB – PersonEntity: Name: NameFull: Panoutsos G IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: 2024 Oct Type: published Y: 2024 Identifiers: – Type: issn-electronic Value: 1879-0534 Numbering: – Type: volume Value: 181 Titles: – TitleFull: Computers in biology and medicine Type: main |
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