Leveraging Machine Learning and Artificial Intelligence to Improve Peripheral Artery Disease Detection, Treatment, and Outcomes

Circ Res. 2021 Jun 11;128(12):1833-1850. doi: 10.1161/CIRCRESAHA.121.318224. Epub 2021 Jun 10.

Abstract

Peripheral artery disease is an atherosclerotic disorder which, when present, portends poor patient outcomes. Low diagnosis rates perpetuate poor management, leading to limb loss and excess rates of cardiovascular morbidity and death. Machine learning algorithms and artificially intelligent systems have shown great promise in application to many areas in health care, such as accurately detecting disease, predicting patient outcomes, and automating image interpretation. Although the application of these technologies to peripheral artery disease are in their infancy, their promises are tremendous. In this review, we provide an introduction to important concepts in the fields of machine learning and artificial intelligence, detail the current state of how these technologies have been applied to peripheral artery disease, and discuss potential areas for future care enhancement with advanced analytics.

Keywords: artificial intelligence; deep learning; machine learning; peripheral artery disease; precision medicine; vascular disease.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Algorithms
  • Aortic Aneurysm / diagnostic imaging
  • Artificial Intelligence* / trends
  • Atherosclerosis / complications
  • Behavior Therapy
  • Carotid Artery Diseases / diagnostic imaging
  • Forecasting
  • Humans
  • Image Interpretation, Computer-Assisted
  • Life Style
  • Machine Learning / trends
  • Natural Language Processing
  • Peripheral Arterial Disease / diagnosis*
  • Peripheral Arterial Disease / diagnostic imaging
  • Peripheral Arterial Disease / etiology
  • Peripheral Arterial Disease / therapy*
  • Phenotype
  • Prognosis
  • Risk Assessment
  • Supervised Machine Learning
  • Treatment Outcome