Blar i forfatter "Attia, Zachi I."

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    • Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes 

      Libiseller-Egger, Julian; Phelan, Jody E.; Attia, Zachi I.; Benavente, Ernest Diez; Campino, Susana; Friedman, Paul A.; Lopez-Jimenez, Francisco; Leon, David A.; Clark, Taane G. (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-12-31)
      Artifcial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expertlevel performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age (“delta age”) to be associated ...

    • Machine-learning-derived heart and brain age are independently associated with cognition 

      Iakunchykova, Olena; Schirmer, Henrik; Vangberg, Torgil Riise; Wang, Yunpeng; Benavente, Ernest D.; van Es, René; van de Leur, Rutger R.; Lindekleiv, Haakon; Attia, Zachi I.; Lopez-Jimenez, Francisco; Leon, David A.; Wilsgaard, Tom (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-05-31)
      Background and purpose - A heart age biomarker has been developed using deep neural networks applied to electrocardiograms. Whether this biomarker is associated with cognitive function was investigated.<p> <p>Methods - Using 12-lead electrocardiograms, heart age was estimated for a population-based sample (N = 7779, age 40–85 years, 45.3% men). Associations between heart delta age (HDA) and ...

    • Studying accelerated cardiovascular ageing in Russian adults through a novel deep-learning ECG biomarker 

      Benavente, Ernest Diez; Jimenez-Lopez, Francisco; Attia, Zachi I.; Malyutina, Sofia; Kudryavtsev, Alexander; Ryabikov, Andrey; Friedman, Paul A.; Kapa, Suraj; Voevoda, Michael; Perel, Pablo; Schirmer, Henrik; Hughes, Alun D.; Clark, Taane; Leon, David A. (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-01-25)
      Background: A non-invasive, easy-to-access marker of accelerated cardiac ageing would provide novel insights into the mechanisms and aetiology of cardiovascular disease (CVD) as well as contribute to risk stratification of those who have not had a heart or circulatory event. Our hypothesis is that differences between an ECG-predicted and chronologic age of participants (δage) would reflect accelerated ...