Category Archives: Clinical

Abstract Background Recent guidelines propose N-terminal pro-B-type natriuretic peptide (NT-proBNP) for recognition of asymptomatic left ventricular (LV) dysfunction (Stage B Heart Failure, SBHF) in type 2 diabetes mellitus (T2DM). Wavelet Transform based signal-processing transforms electrocardiogram (ECG) waveforms into an energy distribution waveform (ew)ECG, providing frequency and energy features that machine learning can use as additional […]

Originally published29 Dec 2023https://doi.org/10.1161/JAHA.123.031671Journal of the American Heart Association. 2024;13:e031671 Link to article: Quantitative Prediction of Right Ventricular Size and Function From the ECG | Journal of the American Heart Association (ahajournals.org)   Abstract Background Right ventricular ejection fraction (RVEF) and end‐diastolic volume (RVEDV) are not readily assessed through traditional modalities. Deep learning–enabled ECG analysis […]

Joshua Lampert, Akhil Vaid, William Whang, Jacob Koruth, Marc A. Miller, Marie-Noelle Langan, Daniel Musikantow, Mohit Turagam, Abhishek Maan, Iwanari Kawamura, Srinivas Dukkipati, Girish N. Nadkarni, and Vivek Y. Reddy J Am Coll Cardiol EP. 2023 Aug, 9 (8_Part_2) 1437–1451 Central Illustration   Abstract Background Premature ventricular complexes (PVCs) are prevalent and, although often benign, they may […]

Akhil Vaid, Joy Jiang, Ashwin Sawant, Stamatios Lerakis, Edgar Argulian, Yuri Ahuja, Joshua Lampert, Alexander Charney, Hayit Greenspan, Jagat Narula, Benjamin Glicksberg & Girish N Nadkarni npj Digital Medicine volume 6, Article number: 108 (2023) Link to article:  A foundational vision transformer improves diagnostic performance for electrocardiograms | npj Digital Medicine (nature.com)   Abstract The electrocardiogram (ECG) is a ubiquitous diagnostic modality. Convolutional neural networks (CNNs) applied towards ECG analysis require large […]

Akhil Vaid, Edgar Argulian, Stamatios Lerakis, Brett K. Beaulieu-Jones, Chayakrit Krittanawong, Eyal Klang, Joshua Lampert, Vivek Y. Reddy, Jagat Narula, Girish N. Nadkarni & Benjamin S. Glicksberg Communications Medicine volume 3, Article number: 24 (2023) Link to article:  Multi-center retrospective cohort study applying deep learning to electrocardiograms to identify left heart valvular dysfunction | Communications Medicine (nature.com)   Abstract Background Aortic Stenosis and Mitral Regurgitation are common valvular conditions representing a […]

Utilizing a wide spectrum of data — traditional and signal processed ECG, patient demographics, and comorbidities — successfully predicted echocardiographically defined patient subgroups at high risk of major adverse cardiovascular events. Results demonstrate the potential value of machine learning-driven algorithms for rapid decision-making in an office-based setting to evaluate and monitor the progress of the […]

Akhil Vaid 1, Kipp W Johnson 2, Marcus A Badgeley 3, Sulaiman S Somani 4, Mesude Bicak 5, Isotta Landi 6, Adam Russak 7, Shan Zhao 8, Matthew A Levin 9, Robert S Freeman 10, Alexander W Charney 11, Atul Kukar 12, Bette Kim 13, Tatyana Danilov 14, Stamatios Lerakis 15, Edgar Argulian 16, Jagat Narula 17, Girish N Nadkarni 18, Benjamin S Glicksberg 19 Affiliations expand Abstract Objectives: This study sought to develop DL models capable of comprehensively quantifying left and right ventricular dysfunction from ECG data in a large, diverse population. Background: Rapid […]

Sulaiman S Somani1, Hossein Honarvar1, Sukrit Narula2, Isotta Landi1, Shawn Lee3, Yeraz Khachatoorian4, Arsalan Rehmani3, Andrew Kim4, Jessica K De Freitas1, Shelly Teng1, Suraj Jaladanki1, Arvind Kumar1, Adam Russak1, Shan P Zhao1, Robert Freeman5, Matthew A Levin6, Girish N Nadkarni1, Alexander C Kagen7, Edgar Argulian3, Benjamin S Glicksberg1 Abstract Aims: Clinical scoring systems for pulmonary embolism (PE) screening have low specificity and contribute to computed tomography pulmonary angiogram (CTPA) overuse. We assessed whether deep learning […]

Demonstrates Potential for ECG screening for LV dysfunction in asymptomatic patients with ejection fraction > 40% SOUTHLAKE, Texas, June 28, 2021 – HeartSciences, a medical device company focused on advancing the field of electrocardiology through innovation, announced the results of a study by Australia’s Baker Heart and Diabetes Institute focused on identifying asymptomatic heart failure […]

To identify whether machine learning from the processing of continuous wave transforms (CWTs) to provide an “energy waveform” electrocardiogram (ewECG) could be integrated with the echocardiographic assessment of subclinical systolic and diastolic left ventricular dysfunction (LVD). Asymptomatic LVD has management implications, but routine echocardiography is not undertaken in subjects at risk of heart failure. Signal […]