Leveling Up: A Review of Machine Learning Models in The Cardiac

Am. J. Med. · Oct 2023

Review

Leveling Up: A Review of Machine Learning Models in The Cardiac ICU.

Machine learning has emerged as a significant tool to augment the medical decision-making process. Studies have steadily accrued detailing algorithms and models designed using machine learning to predict and anticipate pathologic states. The cardiac intensive care unit is an area where anticipation is crucial in the division between life and death. In this paper, we aim to review important studies describing the utility of machine learning algorithms to describe the future of artificial intelligence in the cardiac intensive care unit, especially in regards to the prediction of successful ventilatory weaning, acute respiratory distress syndrome, arrhythmia, and acute kidney injury.

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- Zain Khalpey, Parker Wilson, Yash Suri, Hunter Culbert, Jessa Deckwa, Amina Khalpey, and Brynne Rozell.
- Division of Cardiothoracic Surgery, Heart and Vascular Institute, HonorHealth, Scottsdale, Ariz. Electronic address: zkhalpey@honorhealth.com.
- Am. J. Med. 2023 Oct 1; 136 (10): 979984979-984.
AbstractMachine learning has emerged as a significant tool to augment the medical decision-making process. Studies have steadily accrued detailing algorithms and models designed using machine learning to predict and anticipate pathologic states. The cardiac intensive care unit is an area where anticipation is crucial in the division between life and death. In this paper, we aim to review important studies describing the utility of machine learning algorithms to describe the future of artificial intelligence in the cardiac intensive care unit, especially in regards to the prediction of successful ventilatory weaning, acute respiratory distress syndrome, arrhythmia, and acute kidney injury.Copyright © 2023. Published by Elsevier Inc.

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Leveling Up: A Review of Machine Learning Models in The Cardiac ICU.

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