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Automation, machine learning, and artificial intelligence in echocardiography: A brave new world.

Automation, machine learning, and artificial intelligence (AI) are changing the landscape of echocardiography providing complimentary tools to physicians to enhance patient care. Multiple vendor software programs have incorporated automation to improve accuracy and efficiency of manual tracings. Aut...

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Published in:Echocardiography Vol. 35; no. 9; pp. 1402 - 1419
Main Authors: Gandhi, Sumeet, Mosleh, Wassim, Shen, Joshua, Chow, Chi‐Ming
Format: diagnostic images tables/charts Journal Article
Published: Wiley-Blackwell Sep2018
Online Access:View this record in EBSCOhost
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      dt: Sep2018
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1111/echo.14086
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        atl: Automation, machine learning, and artificial intelligence in echocardiography: A brave new world.
      aug:
        au:
          Gandhi, Sumeet
          Mosleh, Wassim
          Shen, Joshua
          Chow, Chi‐Ming
        affil: Hamilton Health Sciences Centre, McMaster University, Hamilton, Ontario, Canada
      sug:
        subj:
          Automation
          Machine Learning
          Artificial Intelligence
          Echocardiography, Three-Dimensional
          Technology
      ab: Automation, machine learning, and artificial intelligence (AI) are changing the landscape of echocardiography providing complimentary tools to physicians to enhance patient care. Multiple vendor software programs have incorporated automation to improve accuracy and efficiency of manual tracings. Automation with longitudinal strain and 3D echocardiography has shown great accuracy and reproducibility allowing the incorporation of these techniques into daily workflow. This will give further experience to nonexpert readers and allow the integration of these essential tools into more echocardiography laboratories. The potential for machine learning in cardiovascular imaging is still being discovered as algorithms are being created, with training on large data sets beyond what traditional statistical reasoning can handle. Deep learning when applied to large image repositories will recognize complex relationships and patterns integrating all properties of the image, which will unlock further connections about the natural history and prognosis of cardiac disease states. The purpose of this review article was to describe the role and current use of automation, machine learning, and AI in echocardiography and discuss potential limitations and challenges of in the future.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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