Posts Tagged ‘Signal Processing’
Deep Learning-Based Electrocardiogram Analysis Predicts Biventricular Dysfunction and Dilation in Congenital Heart Disease.
Link: https://doi.org/S0735-1097(24)07676-9 Authors: Mayourian, Joshua; Gearhart, Addison; La Cava, William G; Vaid, Akhil; Nadkarni, Girish N; Triedman, John K; Powell, Andrew J; Wald, Rachel M; Valente, Anne Marie; Geva, Tal; Duong, Son Q; Ghelani, Sunil J Abstract: Artificial intelligence-enhanced electrocardiogram (AI-ECG) analysis shows promise to detect biventricular pathophysiology. However, AI-ECG analysis remains underexplored in congenital…
Read MoreArtificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study.
Link: https://doi.org/S2589-7500(24)00249-8 Authors: Oikonomou, Evangelos K; Vaid, Akhil; Holste, Gregory; Coppi, Andreas; McNamara, Robert L; Baloescu, Cristiana; Krumholz, Harlan M; Wang, Zhangyang; Apakama, Donald J; Nadkarni, Girish N; Khera, Rohan Abstract: Point-of-care ultrasonography (POCUS) enables cardiac imaging at the bedside and in communities but is limited by abbreviated protocols and variation in quality. We aimed…
Read MoreDeep Learning for Contrast Enhanced Mammography – A Systematic Review.
Link: https://doi.org/10.1016/j.acra.2024.11.035 Authors: Sorin, Vera; Sklair-Levy, Miri; Glicksberg, Benjamin S; Konen, Eli; Nadkarni, Girish N; Klang, Eyal Abstract: Contrast-enhanced mammography (CEM) is a relatively novel imaging technique that enables both anatomical and functional breast imaging, with improved diagnostic performance compared to standard 2D mammography. The aim of this study is to systematically review the literature…
Read MoreArtificial intelligence-guided detection of under-recognized cardiomyopathies on point-of-care cardiac ultrasound: a multi-center study.
Link: https://doi.org/10.1101/2024.03.10.24304044 Authors: Oikonomou, Evangelos K; Vaid, Akhil; Holste, Gregory; Coppi, Andreas; McNamara, Robert L; Baloescu, Cristiana; Krumholz, Harlan M; Wang, Zhangyang; Apakama, Donald J; Nadkarni, Girish N; Khera, Rohan Abstract: Point-of-care ultrasonography (POCUS) enables cardiac imaging at the bedside and in communities but is limited by abbreviated protocols and variation in quality. We developed…
Read MoreCharacterizing cell type specific transcriptional differences between the living and postmortem human brain.
Link: https://doi.org/10.1101/2024.05.01.24306590 Authors: Vornholt, Eric; Liharska, Lora E; Cheng, Esther; Hashemi, Alice; Park, You Jeong; Ziafat, Kimia; Wilkins, Lillian; Silk, Hannah; Linares, Lisa M; Thompson, Ryan C; Sullivan, Brendan; Moya, Emily; Nadkarni, Girish N; Sebra, Robert; Schadt, Eric E; Kopell, Brian H; Charney, Alexander W; Beckmann, Noam D Abstract: Single-nucleus RNA sequencing (snRNA-seq) is often…
Read MorePediatric ECG-Based Deep Learning to Predict Left Ventricular Dysfunction and Remodeling.
Link: https://doi.org/10.1161/CIRCULATIONAHA.123.067750 Authors: Mayourian, Joshua; La Cava, William G; Vaid, Akhil; Nadkarni, Girish N; Ghelani, Sunil J; Mannix, Rebekah; Geva, Tal; Dionne, Audrey; Alexander, Mark E; Duong, Son Q; Triedman, John K Abstract: Artificial intelligence-enhanced ECG analysis shows promise to detect ventricular dysfunction and remodeling in adult populations. However, its application to pediatric populations remains…
Read MoreValidation of a convolutional neural network that reliably identifies electromyographic compound motor action potentials following train-of-four stimulation: an algorithm development experimental study.
Link: https://doi.org/10.1016/j.bjao.2023.100236 Authors: Epstein, Richard H; Perez, Olivia F; Hofer, Ira S; Renew, J Ross; Brull, Sorin J; Nemes, Réka Abstract: International guidelines recommend quantitative neuromuscular monitoring when administering neuromuscular blocking agents. The train-of-four count is important for determining the depth of block and appropriate reversal agents and doses. However, identifying valid compound motor action…
Read MoreA foundational vision transformer improves diagnostic performance for electrocardiograms.
Link: https://doi.org/10.1038/s41746-023-00840-9 Authors: Vaid, Akhil; Jiang, Joy; Sawant, Ashwin; Lerakis, Stamatios; Argulian, Edgar; Ahuja, Yuri; Lampert, Joshua; Charney, Alexander; Greenspan, Hayit; Narula, Jagat; Glicksberg, Benjamin; Nadkarni, Girish N Abstract: The electrocardiogram (ECG) is a ubiquitous diagnostic modality. Convolutional neural networks (CNNs) applied towards ECG analysis require large sample sizes, and transfer learning approaches for biomedical…
Read MoreNatural Language Processing in Nephrology.
Link: https://doi.org/S1548-5595(22)00128-8 Authors: Van Vleck, Tielman T; Farrell, Douglas; Chan, Lili Abstract: Unstructured data in the electronic health records contain essential patient information. Natural language processing (NLP), teaching a computer to read, allows us to tap into these data without needing the time and effort of manual chart abstraction. The core first step for all…
Read MoreModulation of the Association Between Age and Death by Risk Factor Burden in Critically Ill Patients With COVID-19.
Link: https://doi.org/10.1097/CCE.0000000000000755 Authors: Sunderraj, Ashwin; Cho, Chloe; Cai, Xuan; Gupta, Shruti; Mehta, Rupal; Isakova, Tamara; Leaf, David E; Srivastava, Anand; , Abstract: Older age is a key risk factor for adverse outcomes in critically ill patients with COVID-19. However, few studies have investigated whether preexisting comorbidities and acute physiologic ICU factors modify the association between…
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