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Artificial Intelligence in Nuclear Cardiology: Adding Value to Prognostication

  • Karthik Seetharam
  • Sirish Shresthra
  • James D. Mills
  • Partho P. SenguptaEmail author
Cardiac Nuclear Imaging (A Cuocolo and M Petretta, Section Editors)
  • 43 Downloads
Part of the following topical collections:
  1. Topical Collection on Cardiac Nuclear Imaging

Abstract

Purpose of the Review

Radionuclide myocardial perfusion imaging (MPI) continues to be an accurate and reproducible method of diagnosing obstructive coronary artery disease (CAD) with predictive, prognostic, and economic value. We review the evolutionary potential of machine learning (ML), a subset of artificial intelligence, as an adjunct to MPI.

Recent Findings

Applying the broad scope of ML, including the integration of deep learning, can leverage the knowledge representation and automated reasoning to detect and extrapolate patterns from high-dimensional features of MPI. There is growing evidence to suggest superior abilities of ML over parametric statistical models for predicting the presence of obstructive CAD, the need for revascularization, and the occurrence of major adverse cardiac events including cardiac death.

Summary

ML is uniquely positioned to provide the next great advancement in the field of nuclear cardiology for improving patient-specific risk stratification.

Keywords

Coronary artery disease Myocardial perfusion imaging Machine learning Artificial intelligence Nuclear cardiology 

Notes

Compliance with Ethical Standards

Conflict of Interest

Karthik Seetharam declares that he has no conflict of interest.

Sirish Shresthra declares that he has no conflict of interest.

James D. Mills declares that he has no conflict of interest.

Partho P. Sengupta is a consultant for HeartSciences, Ultromics, Kencor Health.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the mentioned authors.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Karthik Seetharam
    • 1
  • Sirish Shresthra
    • 1
  • James D. Mills
    • 1
  • Partho P. Sengupta
    • 1
    Email author
  1. 1.West Virginia University Medicine Heart and Vascular InstituteMorgantownUSA

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