Posts Tagged ‘Machine Vision’
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 MoreMulti-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 MoreAutoencoders 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 MoreEnhancing 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 MoreFederated 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 MoreAutomated 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 MoreDevelopment 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 MoreIdentification 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 MoreContrastive 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 MoreUsing 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…
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