Big-ECG: Cardiographic Predictive Cyber-Physical System for Stroke Management

Hussain, Iqram; Park, Se Jin

doi:10.1109/ACCESS.2021.3109806

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Big-ECG: Cardiographic Predictive Cyber-Physical System for Stroke Management

Author(s): Iqram Hussain , Se Jin Park

Publication date (Print): 2021

Journal: IEEE Access

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

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Most cited references 53

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Cross-Validatory Choice and Assessment of Statistical Predictions

M. Stone (1974)

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A real-time QRS detection algorithm.

J. Pan, W Tompkins (1985)

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An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction

Zachi Attia, Peter A. Noseworthy, Francisco López-Jiménez … (2019)

Atrial fibrillation is frequently asymptomatic and thus underdetected but is associated with stroke, heart failure, and death. Existing screening methods require prolonged monitoring and are limited by cost and low yield. We aimed to develop a rapid, inexpensive, point-of-care means of identifying patients with atrial fibrillation using machine learning.

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Author and article information

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Iqram Hussain: (View ORCID Profile)

Se Jin Park: (View ORCID Profile)

Journal

Title: IEEE Access

Abbreviated Title: IEEE Access

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

ISSN (Electronic): 2169-3536

Publication date Created: 2021

Publication date (Print): 2021

Volume: 9

Pages: 123146-123164

Article

DOI: 10.1109/ACCESS.2021.3109806

SO-VID: 536041b4-f555-4879-b29a-297d4361b29b

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https://creativecommons.org/licenses/by/4.0/legalcode

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