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Current Cardiology Reports

Key Concepts in Machine Learning and Clinical Applications in the Cardiac Intensive Care Unit

Published in:
Authors
Dhruv Sarma
Aniket S. Rali
Jacob. C. Jentzer
Published in
Current Cardiology Reports | Issue 1/2025

Abstract

Purpose of Review

Artificial Intelligence (AI) technology will significantly alter critical care cardiology, from our understanding of diseases to the way in which we communicate with patients and colleagues. We summarize the potential applications of AI in the cardiac intensive care unit (CICU) by reviewing current evidence, future developments and possible challenges.

Recent Findings

Machine Learning (ML) methods have been leveraged to improve interpretation and discover novel uses for diagnostic tests such as the ECG and echocardiograms. ML-based dynamic risk stratification and prognostication may help optimize triaging and CICU discharge procedures. Latent class analysis and K-means clustering may reveal underlying disease sub-phenotypes within heterogeneous conditions such as cardiogenic shock and decompensated heart failure.

Summary

AI technology may help enhance routine clinical care, facilitate medical education and training, and unlock individualized therapies for patients in the CICU. However, robust regulation and improved clinician understanding of AI is essential to overcome important practical and ethical challenges.
Title
Key Concepts in Machine Learning and Clinical Applications in the Cardiac Intensive Care Unit
Authors
Dhruv Sarma
Aniket S. Rali
Jacob. C. Jentzer
Publication date
01-12-2025
Publisher
Springer US
Published in
Current Cardiology Reports / Issue 1/2025
Print ISSN: 1523-3782
Electronic ISSN: 1534-3170
DOI
https://doi.org/10.1007/s11886-024-02149-9
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This content is intended for healthcare professionals outside of the UK.

Independent Medical Education Grant:
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Image Credits
Abstract graphic of layered, concentric circular shapes in bright green, pink, blue, and purple on a dark blue background. The rings and segments form a complex radial pattern without text/© Springer Health+ IME