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Artificial intelligence and the promise of uplifting echocardiography
  1. Erwan Donal1,
  2. Denisa Muraru2,
  3. Luigi Badano3,4
  1. 1 Cardiology, CHU Rennes, Rennes, Bretagne, France
  2. 2 Department of Cardiac, Thoracic and Vascular Sciences, University of Milan–Bicocca, Milano, Lombardia, Italy
  3. 3 School of Medicine and Surgery, University of Milan–Bicocca, Milano, Italy
  4. 4 Department of Cardiological, Neurological and Metabolic Sciences, Istituto Auxologico Italiano Istituto di Ricovero e Cura a Carattere Scientifico, Milano, Italy
  1. Correspondence to Dr Erwan Donal, Cardiology, CHU Rennes, 35033 Rennes, Bretagne, France; erwan.donal{at}chu-rennes.fr

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Echocardiography is the most frequently used imaging modality to assess patients with cardiac diseases and the one with the most favourable cost/effectiveness ratio. Since its introduction in the clinical arena, echocardiography has changed our understanding of the pathophysiology of many cardiac diseases and the way we assess them, replacing invasive cardiac catheterisation in most of the cases. However, both the acquisition and the interpretation of the echocardiography studies, as well as the reproducibility and the repeatability of the measurements, rely heavily on the expertise and the experience of the operators. This is why the practice of echocardiography is considered to be a mixture of craft and science.

Nowadays, the art of echocardiography is in danger. The progressive ageing of the general population and the related increased prevalence of cardiovascular disease on one end, and the ageing of the operators associated to the time constrain to perform more and more echocardiography studies on the other end, have created an unprecedented time crunch to perform and interpret an increasing number of studies that may lead to burnout and reporting errors. The recent development of artificial intelligence (AI) techniques to make automated segmentation and quantitative analysis of the echocardiography images offer a solution to reduce echocardiographer …

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Footnotes

  • Twitter @lpbadano

  • Contributors All the authors contributed significantly to the writing of the manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Provenance and peer review Commissioned; internally peer reviewed.

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