The Use of Artificial Intelligence to Predict the Development of Atrial Fibrillation

被引：0
|
作者：
Daniel Pipilas
Samuel Freesun Friedman
Shaan Khurshid
机构：
[1] Massachusetts General Hospital,Cardiovascular Research Center
[2] Broad Institute of Harvard University and the Massachusetts Institute of Technology,Cardiovascular Disease Initiative
[3] Massachusetts General Hospital,Division of Cardiology
[4] Massachusetts General Hospital,Demoulas Center for Cardiac Arrhythmias
[5] Broad Institute of Harvard University and the Massachusetts Institute of Technology,Data Sciences Platform
来源：
Current Cardiology Reports | 2023年 / 25卷
关键词：
Atrial fibrillation; Artificial intelligence; Machine learning; Risk prediction;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：381 / 389
页数：8
相关论文
共 50 条
  • [1] The Use of Artificial Intelligence to Predict the Development of Atrial Fibrillation
    Pipilas, Daniel
    Friedman, Samuel Freesun
    Khurshid, Shaan
    [J]. CURRENT CARDIOLOGY REPORTS, 2023, 25 (05) : 381 - 389
  • [2] Artificial intelligence and atrial fibrillation
    Sehrawat, Ojasav
    Kashou, Anthony H.
    Noseworthy, Peter A.
    [J]. JOURNAL OF CARDIOVASCULAR ELECTROPHYSIOLOGY, 2022, 33 (08) : 1932 - 1943
  • [3] Use of Artificial Intelligence Electrocardiography to Predict Atrial Fibrillation (AF) in Patients with Chronic Lymphocytic Leukemia (CLL)
    Christopoulos, Georgios
    Attia, Zachi I.
    Noseworthy, Peter A.
    Call, Timothy G.
    Ding, Wei
    Leis, Jose F.
    Muchtar, Eli
    Kenderian, Saad S.
    Wang, Yucai
    Koehler, Amber
    Kay, Neil E.
    Kapoor, Prashant
    Friedman, Paul A.
    Herrmann, Joerg
    Parikh, Sameer A.
    [J]. BLOOD, 2020, 136
  • [4] Artificial intelligence for early atrial fibrillation detection
    Fabritz, Larissa
    Obergassel, Julius
    [J]. LANCET, 2022, 400 (10359): : 1173 - 1175
  • [5] Artificial Intelligence for the Detection and Treatment of Atrial Fibrillation
    Harmon, David M.
    Sehrawat, Ojasav
    Maanja, Maren
    Wight, John
    Noseworthy, Peter A.
    [J]. ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW, 2023, 12
  • [6] Artificial Intelligence-Electrocardiography to Predict Incident Atrial Fibrillation A Population-Based Study
    Christopoulos, Georgios
    Graff-Radford, Jonathan
    Lopez, Camden L.
    Yao, Xiaoxi
    Attia, Zachi, I
    Rabinstein, Alejandro A.
    Petersen, Ronald C.
    Knopman, David S.
    Mielke, Michelle M.
    Kremers, Walter
    Vemuri, Prashanthi
    Siontis, Konstantinos C.
    Friedman, Paul A.
    Noseworthy, Peter A.
    [J]. CIRCULATION-ARRHYTHMIA AND ELECTROPHYSIOLOGY, 2020, 13 (12): : E009355
  • [7] DEVELOPMENT OF ARTIFICIAL INTELLIGENCE-BASED 12-LEAD AND SINGLE-LEAD ELECTROCARDIOGRAM MODELS TO PREDICT ATRIAL FIBRILLATION
    Zhu, Xiaoqing
    Guo, Jun
    [J]. JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2024, 83 (13) : 195 - 195
  • [8] Artificial intelligence for a personalized diagnosis and treatment of atrial fibrillation
    Sanchez de la Nava, Ana Maria
    Atienza, Felipe
    Bermejo, Javier
    Fernandez-Aviles, Francisco
    [J]. AMERICAN JOURNAL OF PHYSIOLOGY-HEART AND CIRCULATORY PHYSIOLOGY, 2021, 320 (04): : H1337 - H1347
  • [9] Artificial Intelligence-Electrocardiography to Predict Time to Atrial Fibrillation: An Analysis of Mayo Clinic Study of Aging
    Christopoulos, Georgios
    Lopez, Camden L.
    Yao, Xiaoxi
    Attia, Zachi I.
    Graff-Radford, Jonathan
    Rabinstein, Alejandro A.
    Ronald, Petersen C.
    Knopman, David
    Mielke, Michelle M.
    Kremers, Walter
    Friedman, Paul
    Noseworthy, Peter A.
    [J]. CIRCULATION, 2020, 142
  • [10] Artificial intelligence analysis of ECG signals to predict arrhythmia recurrence after cryoballoon ablation of atrial fibrillation
    Warminski, G.
    Kalinczuk, L.
    Orczykowski, M.
    Urbanek, P.
    Bodalski, R.
    Zielinski, K.
    Gandor, M.
    Palka, F.
    Jaworski, M.
    Mintz, G. S.
    Kowalik, I.
    Hasiec, A.
    Bilinska, M.
    Plawiak, P.
    Szumowski, L.
    [J]. EUROPEAN HEART JOURNAL, 2022, 43 : 559 - 559
12345