Elsevier

JACC: Heart Failure

Volume 10, Issue 9, September 2022, Pages 603-622
JACC: Heart Failure

State-of-the-Art Review
Contemporary Applications of Machine Learning for Device Therapy in Heart Failure

https://doi.org/10.1016/j.jchf.2022.06.011Get rights and content
Under an Elsevier user license
open archive

Highlights

  • While actuating exemplary changes, clinical gaps exist in the domain of device therapy in heart failure.

  • Machine learning has been postulated to improve candidate selection and outcomes for device therapy.

  • Integration of machine learning with current clinical practices can further the idea of precision medicine.

  • Data integration and model interpretability are the major challenges preventing widespread assimilation into clinical practice.

Abstract

Despite a better understanding of the underlying pathogenesis of heart failure (HF), pharmacotherapy, surgical, and percutaneous interventions do not prevent disease progression in all patients, and a significant proportion of patients end up requiring advanced therapies. Machine learning (ML) is gaining wider acceptance in cardiovascular medicine because of its ability to incorporate large, complex, and multidimensional data and to potentially facilitate the creation of predictive models not constrained by many of the limitations of traditional statistical approaches. With the coexistence of “big data” and novel advanced analytic techniques using ML, there is ever-increasing research into applying ML in the context of HF with the goal of improving patient outcomes. Through this review, the authors describe the basics of ML and summarize the existing published reports regarding contemporary applications of ML in device therapy for HF while highlighting the limitations to widespread implementation and its future promises.

Key Words

cardiac resynchronization therapy
echocardiography
heart failure
left ventricular assist device
machine learning
transcatheter edge-to-edge repair

Abbreviations and Acronyms

AI
artificial intelligence
CRT
cardiac resynchronization therapy
ECG
electrocardiography
HF
heart failure
ICD
implantable cardiac defibrillator
LV
left ventricle
LVAD
left ventricular assist device
ML
machine learning
PAP
pulmonary artery pressure
PCWP
pulmonary capillary wedge pressure
RV
right ventricle
TEE
transesophageal echocardiogram
TEER
transcatheter edge-to-edge repair

Cited by (0)

The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the Author Center.