Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts.
Saved in:
| Title: | Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts. |
|---|---|
| Authors: | Fremond S; Department of Pathology, Leiden University Medical Center, Leiden, Netherlands., Andani S; Department of Computer Science, ETH Zurich, Zurich, Switzerland; Department of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland., Barkey Wolf J; Department of Pathology, Leiden University Medical Center, Leiden, Netherlands., Dijkstra J; Department of Vascular and Molecular Imaging, Leiden University Medical Center, Leiden, Netherlands., Melsbach S; Department of Pathology, Leiden University Medical Center, Leiden, Netherlands., Jobsen JJ; Department of Radiation Oncology, Medisch Spectrum Twente, Enschede, Netherlands., Brinkhuis M; Department of Pathology, LabPON, Hengelo, Netherlands., Roothaan S; Department of Pathology, LabPON, Hengelo, Netherlands., Jurgenliemk-Schulz I; Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands., Lutgens LCHW; Department of Radiation Oncology, Maastricht University Medical Center+, Maastricht, Netherlands., Nout RA; Department of Radiation Oncology, Erasmus University Medical Center, Rotterdam, Netherlands., van der Steen-Banasik EM; Department of Radiation Oncology, Radiotherapiegroep, Arnhem, Netherlands., de Boer SM; Department of Radiation Oncology, Leiden University Medical Center, Leiden, Netherlands., Powell ME; Department of Clinical Oncology, Barts Health NHS Trust, London, UK., Singh N; Department of Pathology, Barts Health NHS Trust, London, UK., Mileshkin LR; Department of Medical Oncology, Peter MacCallum Cancer Center, Melbourne, VIC, Australia., Mackay HJ; Department of Medical Oncology and Hematology, Odette Cancer Center Sunnybrook Health Sciences Center, Toronto, ON, Canada., Leary A; Medical Oncology Department, Gustave Roussy Institute, Villejuif, France., Nijman HW; Department of Obstetrics and Gynecology, University Medical Center Groningen, Groningen, Netherlands., Smit VTHBM; Department of Pathology, Leiden University Medical Center, Leiden, Netherlands., Creutzberg CL; Department of Radiation Oncology, Leiden University Medical Center, Leiden, Netherlands., Horeweg N; Department of Radiation Oncology, Leiden University Medical Center, Leiden, Netherlands., Koelzer VH; Department of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland. Electronic address: viktor.koelzer@usz.ch., Bosse T; Department of Pathology, Leiden University Medical Center, Leiden, Netherlands. Electronic address: t.bosse@lumc.nl. |
| Source: | The Lancet. Digital health [Lancet Digit Health] 2023 Feb; Vol. 5 (2), pp. e71-e82. Date of Electronic Publication: 2022 Dec 07. |
| Publication Type: | Randomized Controlled Trial; Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Elsevier Ltd Country of Publication: England NLM ID: 101751302 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2589-7500 (Electronic) Linking ISSN: 25897500 NLM ISO Abbreviation: Lancet Digit Health Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 36496303 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Fremond+S%22">Fremond S</searchLink>; Department of Pathology, Leiden University Medical Center, Leiden, Netherlands.<br /><searchLink fieldCode="AU" term="%22Andani+S%22">Andani S</searchLink>; Department of Computer Science, ETH Zurich, Zurich, Switzerland; Department of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.<br /><searchLink fieldCode="AU" term="%22Barkey+Wolf+J%22">Barkey Wolf J</searchLink>; Department of Pathology, Leiden University Medical Center, Leiden, Netherlands.<br /><searchLink fieldCode="AU" term="%22Dijkstra+J%22">Dijkstra J</searchLink>; Department of Vascular and Molecular Imaging, Leiden University Medical Center, Leiden, Netherlands.<br /><searchLink fieldCode="AU" term="%22Melsbach+S%22">Melsbach S</searchLink>; Department of Pathology, Leiden University Medical Center, Leiden, Netherlands.<br /><searchLink fieldCode="AU" term="%22Jobsen+JJ%22">Jobsen JJ</searchLink>; Department of Radiation Oncology, Medisch Spectrum Twente, Enschede, Netherlands.<br /><searchLink fieldCode="AU" term="%22Brinkhuis+M%22">Brinkhuis M</searchLink>; Department of Pathology, LabPON, Hengelo, Netherlands.<br /><searchLink fieldCode="AU" term="%22Roothaan+S%22">Roothaan S</searchLink>; Department of Pathology, LabPON, Hengelo, Netherlands.<br /><searchLink fieldCode="AU" term="%22Jurgenliemk-Schulz+I%22">Jurgenliemk-Schulz I</searchLink>; Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands.<br /><searchLink fieldCode="AU" term="%22Lutgens+LCHW%22">Lutgens LCHW</searchLink>; Department of Radiation Oncology, Maastricht University Medical Center+, Maastricht, Netherlands.<br /><searchLink fieldCode="AU" term="%22Nout+RA%22">Nout RA</searchLink>; Department of Radiation Oncology, Erasmus University Medical Center, Rotterdam, Netherlands.<br /><searchLink fieldCode="AU" term="%22van+der+Steen-Banasik+EM%22">van der Steen-Banasik EM</searchLink>; Department of Radiation Oncology, Radiotherapiegroep, Arnhem, Netherlands.<br /><searchLink fieldCode="AU" term="%22de+Boer+SM%22">de Boer SM</searchLink>; Department of Radiation Oncology, Leiden University Medical Center, Leiden, Netherlands.<br /><searchLink fieldCode="AU" term="%22Powell+ME%22">Powell ME</searchLink>; Department of Clinical Oncology, Barts Health NHS Trust, London, UK.<br /><searchLink fieldCode="AU" term="%22Singh+N%22">Singh N</searchLink>; Department of Pathology, Barts Health NHS Trust, London, UK.<br /><searchLink fieldCode="AU" term="%22Mileshkin+LR%22">Mileshkin LR</searchLink>; Department of Medical Oncology, Peter MacCallum Cancer Center, Melbourne, VIC, Australia.<br /><searchLink fieldCode="AU" term="%22Mackay+HJ%22">Mackay HJ</searchLink>; Department of Medical Oncology and Hematology, Odette Cancer Center Sunnybrook Health Sciences Center, Toronto, ON, Canada.<br /><searchLink fieldCode="AU" term="%22Leary+A%22">Leary A</searchLink>; Medical Oncology Department, Gustave Roussy Institute, Villejuif, France.<br /><searchLink fieldCode="AU" term="%22Nijman+HW%22">Nijman HW</searchLink>; Department of Obstetrics and Gynecology, University Medical Center Groningen, Groningen, Netherlands.<br /><searchLink fieldCode="AU" term="%22Smit+VTHBM%22">Smit VTHBM</searchLink>; Department of Pathology, Leiden University Medical Center, Leiden, Netherlands.<br /><searchLink fieldCode="AU" term="%22Creutzberg+CL%22">Creutzberg CL</searchLink>; Department of Radiation Oncology, Leiden University Medical Center, Leiden, Netherlands.<br /><searchLink fieldCode="AU" term="%22Horeweg+N%22">Horeweg N</searchLink>; Department of Radiation Oncology, Leiden University Medical Center, Leiden, Netherlands.<br /><searchLink fieldCode="AU" term="%22Koelzer+VH%22">Koelzer VH</searchLink>; Department of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland. Electronic address: viktor.koelzer@usz.ch.<br /><searchLink fieldCode="AU" term="%22Bosse+T%22">Bosse T</searchLink>; Department of Pathology, Leiden University Medical Center, Leiden, Netherlands. Electronic address: t.bosse@lumc.nl. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101751302%22">The Lancet. Digital health</searchLink> [Lancet Digit Health] 2023 Feb; Vol. 5 (2), pp. e71-e82. <i>Date of Electronic Publication: </i>2022 Dec 07. – Name: TypePub Label: Publication Type Group: TypPub Data: Randomized Controlled Trial; 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+Ltd%22">Elsevier Ltd </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101751302 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2589-7500 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2225897500%22">25897500 </searchLink><i>NLM ISO Abbreviation: </i>Lancet Digit Health <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=36496303 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/S2589-7500(22)00210-2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: e71 Titles: – TitleFull: Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Fremond S – PersonEntity: Name: NameFull: Andani S – PersonEntity: Name: NameFull: Barkey Wolf J – PersonEntity: Name: NameFull: Dijkstra J – PersonEntity: Name: NameFull: Melsbach S – PersonEntity: Name: NameFull: Jobsen JJ – PersonEntity: Name: NameFull: Brinkhuis M – PersonEntity: Name: NameFull: Roothaan S – PersonEntity: Name: NameFull: Jurgenliemk-Schulz I – PersonEntity: Name: NameFull: Lutgens LCHW – PersonEntity: Name: NameFull: Nout RA – PersonEntity: Name: NameFull: van der Steen-Banasik EM – PersonEntity: Name: NameFull: de Boer SM – PersonEntity: Name: NameFull: Powell ME – PersonEntity: Name: NameFull: Singh N – PersonEntity: Name: NameFull: Mileshkin LR – PersonEntity: Name: NameFull: Mackay HJ – PersonEntity: Name: NameFull: Leary A – PersonEntity: Name: NameFull: Nijman HW – PersonEntity: Name: NameFull: Smit VTHBM – PersonEntity: Name: NameFull: Creutzberg CL – PersonEntity: Name: NameFull: Horeweg N – PersonEntity: Name: NameFull: Koelzer VH – PersonEntity: Name: NameFull: Bosse T IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: 2023 Feb Type: published Y: 2023 Identifiers: – Type: issn-electronic Value: 2589-7500 Numbering: – Type: volume Value: 5 – Type: issue Value: 2 Titles: – TitleFull: The Lancet. Digital health Type: main |
| ResultId | 1 |
