Deep learning and the electrocardiogram: review of the current state-of-the-art.

Link: https://doi.org/10.1093/europace/euaa377 Authors: Somani, Sulaiman; Russak, Adam J; Richter, Felix; Zhao, Shan; Vaid, Akhil; Chaudhry, Fayzan; De Freitas, Jessica K; Naik, Nidhi; Miotto, Riccardo; Nadkarni, Girish N; Narula, Jagat; Argulian, Edgar; Glicksberg, Benjamin S Abstract: In the recent decade, deep learning, a subset of artificial intelligence and machine learning, has been used to identify patterns…

Read More

Multi-center retrospective cohort study applying deep learning to electrocardiograms to identify left heart valvular dysfunction.

Link: https://doi.org/10.1038/s43856-023-00240-w Authors: Vaid, Akhil; Argulian, Edgar; Lerakis, Stamatios; Beaulieu-Jones, Brett K; Krittanawong, Chayakrit; Klang, Eyal; Lampert, Joshua; Reddy, Vivek Y; Narula, Jagat; Nadkarni, Girish N; Glicksberg, Benjamin S Abstract: Aortic Stenosis and Mitral Regurgitation are common valvular conditions representing a hidden burden of disease within the population. The aim of this study was to…

Read More

Autoencoders for sample size estimation for fully connected neural network classifiers.

Link: https://doi.org/10.1038/s41746-022-00728-0 Authors: Gulamali, Faris F; Sawant, Ashwin S; Kovatch, Patricia; Glicksberg, Benjamin; Charney, Alexander; Nadkarni, Girish N; Oermann, Eric Abstract: Sample size estimation is a crucial step in experimental design but is understudied in the context of deep learning. Currently, estimating the quantity of labeled data needed to train a classifier to a desired…

Read More

Enhancing convolutional neural network predictions of electrocardiograms with left ventricular dysfunction using a novel sub-waveform representation.

Link: https://doi.org/10.1016/j.cvdhj.2022.07.074 Authors: Honarvar, Hossein; Agarwal, Chirag; Somani, Sulaiman; Vaid, Akhil; Lampert, Joshua; Wanyan, Tingyi; Reddy, Vivek Y; Nadkarni, Girish N; Miotto, Riccardo; Zitnik, Marinka; Wang, Fei; Glicksberg, Benjamin S Abstract: Electrocardiogram (ECG) deep learning (DL) has promise to improve the outcomes of patients with cardiovascular abnormalities. In ECG DL, researchers often use convolutional neural…

Read More

Federated Learning in Risk Prediction: A Primer and Application to COVID-19-Associated Acute Kidney Injury.

Link: https://doi.org/10.1159/000525645 Authors: Gulamali, Faris F; Nadkarni, Girish N Abstract: Modern machine learning and deep learning algorithms require large amounts of data; however, data sharing between multiple healthcare institutions is limited by privacy and security concerns. Federated learning provides a functional alternative to the single-institution approach while avoiding the pitfalls of data sharing. In cross-silo…

Read More

Automated Determination of Left Ventricular Function Using Electrocardiogram Data in Patients on Maintenance Hemodialysis.

Link: https://doi.org/10.2215/CJN.16481221 Authors: Vaid, Akhil; Jiang, Joy J; Sawant, Ashwin; Singh, Karandeep; Kovatch, Patricia; Charney, Alexander W; Charytan, David M; Divers, Jasmin; Glicksberg, Benjamin S; Chan, Lili; Nadkarni, Girish N Abstract: Left ventricular ejection fraction is disrupted in patients on maintenance hemodialysis and can be estimated using deep learning models on electrocardiograms. Smaller sample sizes…

Read More

Development of a machine learning model using electrocardiogram signals to improve acute pulmonary embolism screening.

Link: https://doi.org/10.1093/ehjdh/ztab101 Authors: Somani, Sulaiman S; Honarvar, Hossein; Narula, Sukrit; Landi, Isotta; Lee, Shawn; Khachatoorian, Yeraz; Rehmani, Arsalan; Kim, Andrew; De Freitas, Jessica K; Teng, Shelly; Jaladanki, Suraj; Kumar, Arvind; Russak, Adam; Zhao, Shan P; Freeman, Robert; Levin, Matthew A; Nadkarni, Girish N; Kagen, Alexander C; Argulian, Edgar; Glicksberg, Benjamin S Abstract: Clinical scoring systems…

Read More

Identification of discriminative gene-level and protein-level features associated with pathogenic gain-of-function and loss-of-function variants.

Link: https://doi.org/S0002-9297(21)00384-0 Authors: Sevim Bayrak, Cigdem; Stein, David; Jain, Aayushee; Chaudhary, Kumardeep; Nadkarni, Girish N; Van Vleck, Tielman T; Puel, Anne; Boisson-Dupuis, Stephanie; Okada, Satoshi; Stenson, Peter D; Cooper, David N; Schlessinger, Avner; Itan, Yuval Abstract: Identifying whether a given genetic mutation results in a gene product with increased (gain-of-function; GOF) or diminished (loss-of-function; LOF)…

Read More

Contrastive learning improves critical event prediction in COVID-19 patients.

Link: https://doi.org/10.1016/j.patter.2021.100389 Authors: Wanyan, Tingyi; Honarvar, Hossein; Jaladanki, Suraj K; Zang, Chengxi; Naik, Nidhi; Somani, Sulaiman; De Freitas, Jessica K; Paranjpe, Ishan; Vaid, Akhil; Zhang, Jing; Miotto, Riccardo; Wang, Zhangyang; Nadkarni, Girish N; Zitnik, Marinka; Azad, Ariful; Wang, Fei; Ding, Ying; Glicksberg, Benjamin S Abstract: Deep learning (DL) models typically require large-scale, balanced training data…

Read More

Using Deep-Learning Algorithms to Simultaneously Identify Right and Left Ventricular Dysfunction From the Electrocardiogram.

Link: https://doi.org/S1936-878X(21)00627-6 Authors: Vaid, Akhil; Johnson, Kipp W; Badgeley, Marcus A; Somani, Sulaiman S; Bicak, Mesude; Landi, Isotta; Russak, Adam; Zhao, Shan; Levin, Matthew A; Freeman, Robert S; Charney, Alexander W; Kukar, Atul; Kim, Bette; Danilov, Tatyana; Lerakis, Stamatios; Argulian, Edgar; Narula, Jagat; Nadkarni, Girish N; Glicksberg, Benjamin S Abstract: This study sought to develop…

Read More