A comparison of artificial intelligence-enhanced electrocardiography approaches for the prediction of time to mortality using electrocardiogram images.
Saved in:
| Title: | A comparison of artificial intelligence-enhanced electrocardiography approaches for the prediction of time to mortality using electrocardiogram images. |
|---|---|
| Authors: | Sau A; National Heart and Lung Institute, Imperial College London, London, UK.; Department of Cardiology, Imperial College Healthcare NHS Trust, London, UK., Zeidaabadi B; National Heart and Lung Institute, Imperial College London, London, UK., Patlatzoglou K; National Heart and Lung Institute, Imperial College London, London, UK., Pastika L; National Heart and Lung Institute, Imperial College London, London, UK., Ribeiro AH; Department of Information Technology, Uppsala University, Uppsala, Sweden., Sabino E; Department of Infectious Diseases, School of Medicine and Institute of Tropical Medicine, University of São Paulo, São Paulo, Brazil., Peters NS; National Heart and Lung Institute, Imperial College London, London, UK.; Department of Cardiology, Imperial College Healthcare NHS Trust, London, UK., Ribeiro ALP; Department of Internal Medicine, Faculdade de Medicina, and Telehealth Centre and Cardiology Service, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil., Kramer DB; National Heart and Lung Institute, Imperial College London, London, UK.; Richard A. and Susan F. Smith Centre for Outcomes Research in Cardiology, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA., Waks JW; Harvard-Thorndike Electrophysiology Institute, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA., Ng FS; National Heart and Lung Institute, Imperial College London, London, UK.; Department of Cardiology, Imperial College Healthcare NHS Trust, London, UK.; Department of Cardiology, Chelsea and Westminster Hospital NHS Foundation Trust, London, UK. |
| Source: | European heart journal. Digital health [Eur Heart J Digit Health] 2024 Nov 18; Vol. 6 (2), pp. 180-189. Date of Electronic Publication: 2024 Nov 18 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 101778323 Publication Model: eCollection Cited Medium: Internet ISSN: 2634-3916 (Electronic) Linking ISSN: 26343916 NLM ISO Abbreviation: Eur Heart J Digit Health Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 40110221 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: A comparison of artificial intelligence-enhanced electrocardiography approaches for the prediction of time to mortality using electrocardiogram images. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Sau+A%22">Sau A</searchLink>; National Heart and Lung Institute, Imperial College London, London, UK.; Department of Cardiology, Imperial College Healthcare NHS Trust, London, UK.<br /><searchLink fieldCode="AU" term="%22Zeidaabadi+B%22">Zeidaabadi B</searchLink>; National Heart and Lung Institute, Imperial College London, London, UK.<br /><searchLink fieldCode="AU" term="%22Patlatzoglou+K%22">Patlatzoglou K</searchLink>; National Heart and Lung Institute, Imperial College London, London, UK.<br /><searchLink fieldCode="AU" term="%22Pastika+L%22">Pastika L</searchLink>; National Heart and Lung Institute, Imperial College London, London, UK.<br /><searchLink fieldCode="AU" term="%22Ribeiro+AH%22">Ribeiro AH</searchLink>; Department of Information Technology, Uppsala University, Uppsala, Sweden.<br /><searchLink fieldCode="AU" term="%22Sabino+E%22">Sabino E</searchLink>; Department of Infectious Diseases, School of Medicine and Institute of Tropical Medicine, University of São Paulo, São Paulo, Brazil.<br /><searchLink fieldCode="AU" term="%22Peters+NS%22">Peters NS</searchLink>; National Heart and Lung Institute, Imperial College London, London, UK.; Department of Cardiology, Imperial College Healthcare NHS Trust, London, UK.<br /><searchLink fieldCode="AU" term="%22Ribeiro+ALP%22">Ribeiro ALP</searchLink>; Department of Internal Medicine, Faculdade de Medicina, and Telehealth Centre and Cardiology Service, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.<br /><searchLink fieldCode="AU" term="%22Kramer+DB%22">Kramer DB</searchLink>; National Heart and Lung Institute, Imperial College London, London, UK.; Richard A. and Susan F. Smith Centre for Outcomes Research in Cardiology, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Waks+JW%22">Waks JW</searchLink>; Harvard-Thorndike Electrophysiology Institute, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA.<br /><searchLink fieldCode="AU" term="%22Ng+FS%22">Ng FS</searchLink>; National Heart and Lung Institute, Imperial College London, London, UK.; Department of Cardiology, Imperial College Healthcare NHS Trust, London, UK.; Department of Cardiology, Chelsea and Westminster Hospital NHS Foundation Trust, London, UK. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101778323%22">European heart journal. Digital health</searchLink> [Eur Heart J Digit Health] 2024 Nov 18; Vol. 6 (2), pp. 180-189. <i>Date of Electronic Publication: </i>2024 Nov 18 (<i>Print Publication: </i>2025). – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Oxford+University+Press%22">Oxford University Press </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101778323 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>2634-3916 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2226343916%22">26343916 </searchLink><i>NLM ISO Abbreviation: </i>Eur Heart J Digit Health <i>Subsets: </i>PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=40110221 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/ehjdh/ztae090 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 180 Titles: – TitleFull: A comparison of artificial intelligence-enhanced electrocardiography approaches for the prediction of time to mortality using electrocardiogram images. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sau A – PersonEntity: Name: NameFull: Zeidaabadi B – PersonEntity: Name: NameFull: Patlatzoglou K – PersonEntity: Name: NameFull: Pastika L – PersonEntity: Name: NameFull: Ribeiro AH – PersonEntity: Name: NameFull: Sabino E – PersonEntity: Name: NameFull: Peters NS – PersonEntity: Name: NameFull: Ribeiro ALP – PersonEntity: Name: NameFull: Kramer DB – PersonEntity: Name: NameFull: Waks JW – PersonEntity: Name: NameFull: Ng FS IsPartOfRelationships: – BibEntity: Dates: – D: 18 M: 11 Text: 2024 Nov 18 Type: published Y: 2024 Identifiers: – Type: issn-electronic Value: 2634-3916 Numbering: – Type: volume Value: 6 – Type: issue Value: 2 Titles: – TitleFull: European heart journal. Digital health Type: main |
| ResultId | 1 |