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Open Access

Peer-reviewed

Research Article

Enhancing machine learning performance in cardiac surgery ICU: Hyperparameter optimization with metaheuristic algorithm

Ali Bahrami,

Roles Conceptualization, Data curation, Methodology, Software, Validation, Visualization, Writing – original draft

Affiliation School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
⨯
Morteza Rakhshaninejad,

Roles Conceptualization, Methodology, Software, Visualization, Writing – original draft

Affiliation School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

https://orcid.org/0000-0001-5250-9165

⨯
Rouzbeh Ghousi ,

Roles Conceptualization, Methodology, Supervision, Writing – review & editing

* E-mail: ghousi@iust.ac.ir

Affiliation School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

https://orcid.org/0000-0002-5839-5792

⨯
Alireza Atashi

Roles Conceptualization, Data curation, Methodology, Resources, Validation, Writing – review & editing

Affiliations Department of Digital Health, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran, Cancer Informatics Research Group, Clinical Research Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran
⨯

Enhancing machine learning performance in cardiac surgery ICU: Hyperparameter optimization with metaheuristic algorithm

Ali Bahrami,
Morteza Rakhshaninejad,
Rouzbeh Ghousi,
Alireza Atashi

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Published: February 10, 2025
https://doi.org/10.1371/journal.pone.0311250

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Ventilators
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Artificial neural networks
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Cardiac surgery
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Death rates
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Algorithms
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Intensive care units
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Machine learning algorithms
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Optimization
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