Literature DB >> 31537342

Development of an Artificially Intelligent Mobile Phone Application to Identify Cardiac Devices on Chest Radiography.

Michael Weinreich, Jay J Chudow, Brian Weinreich, Talia Krumerman, Tonusri Nag, Kusha Rahgozar, Eric Shulman, John Fisher, Kevin J Ferrick.   

Abstract

Year:  2019        PMID： 31537342     DOI： 10.1016/j.jacep.2019.05.013

Source DB:  PubMed          Journal:  JACC Clin Electrophysiol        ISSN： 2405-500X


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  3 in total

Review 1.  Novel Artificial Intelligence Applications in Cardiology: Current Landscape, Limitations, and the Road to Real-World Applications.

Authors:  Frédéric Lesage; Robert Avram; Élodie Labrecque Langlais; Pascal Thériault-Lauzier; Guillaume Marquis-Gravel; Merve Kulbay; Derek Y So; Jean-François Tanguay; Hung Q Ly; Richard Gallo
Journal:  J Cardiovasc Transl Res       Date:  2022-04-22       Impact factor: 4.132

2.  Analysis of Potential for User Errors in Mobile Deployment of Radiology Deep Learning for Cardiac Rhythm Device Detection.

Authors:  Carl Sabottke; Marc Breaux; Rebecca Lee; Adam Foreman; Bradley Spieler
Journal:  J Digit Imaging       Date:  2021-03-19       Impact factor: 4.903

3.  Radiographic Identification of Cardiac Implantable Electronic Device Manufacturer: Smartphone Pacemaker-ID Application Versus X-ray Logo.

Authors:  Bridget Boyle; Charles J Love; Joseph E Marine; Jonathan Chrispin; Andreas S Barth; John W Rickard; David D Spragg; Ronald Berger; Hugh Calkins; Sunil K Sinha
Journal:  J Innov Card Rhythm Manag       Date:  2022-08-15
  3 in total

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