23+ peer-reviewed publications in leading cardiology journals validating our AI-ECG technology for early detection of heart disease.
"\nA foundational vision transformer improves diagnostic performance for electrocardiograms\nJune 6, 2023\n\nAkhil Vaid, Joy Jiang, Ashwin Sawant, Stamatios Lerakis, Edgar Argulian, Yuri Ahuja, Joshua...
Read Publication"\nA Novel ECG-Based Deep Learning Algorithm to Predict Cardiomyopathy in Patients With Premature Ventricular Complexes\nAugust 9, 2023\nJoshua Lampert, Akhil Vaid, William Whang, Jacob Koruth, Marc A...
Read Publication"\nDevelopment of a machine learning model using electrocardiogram signals to improve acute pulmonary embolism screening\nNovember 25, 2021\nSulaiman S Somani1, Hossein Honarvar1, Sukrit Narula2, Isot...
Read Publication"\nDigital Phenotyping of Myocardial Dysfunction With 12-Lead ECG Tiptoeing Into the Future With Machine Learning* (JACC Editorial) – Vol. 76, No.
Read Publication"\nDigital Phenotyping of Myocardial Dysfunction With 12-Lead ECG Tiptoeing Into the Future With Machine Learning* (JACC Editorial) – Vol. 76, No.
Read Publication"\nElectrocardiogram-Based Machine Learning Emulator Model for Predicting Novel Echocardiography-Derived Phenogroups for Cardiac Risk-Stratification: A Prospective Multicenter Cohort Study – Advocate ...
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