Blar i forfatter Det helsevitenskapelige fakultet "Lopez-Jimenez, Francisco"

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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 ...

    • External validation of a deep learning electrocardiogram algorithm to detect ventricular dysfunction 

      Attia, Itzhak Zachi; Tseng, Andrew S.; Benavente, Ernest Diez; Medina-Inojosa, Jose R.; Clark, Taane; Malyutina, Sofia; Kapa, Suraj; Schirmer, Henrik; Kudryavtsev, Alexander V; Noseworthy, Peter A.; Carter, Rickey E.; Ryabikov, Andrey; Perel, Pablo; Friedman, Paul A.; Leon, David A.; Lopez-Jimenez, Francisco (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-01-02)
      Objective - To validate a novel artificial-intelligence electrocardiogram algorithm (AI-ECG) to detect left ventricular systolic dysfunction (LVSD) in an external population.<p> <p>Background - LVSD, even when asymptomatic, confers increased morbidity and mortality. We recently derived AI-ECG to detect LVSD using ECGs based on a large sample of patients treated at the Mayo Clinic.<p> <p>Methods ...

    • 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 ...