Machine Learning Analysis of Identifies Polyunsaturated Fatty Acid Metabolites Predictive of Adverse Outcomes In Heart Failure with Preserved Ejection Fraction Patients
DOI:
https://doi.org/10.46570/utjms.vol11-2023-951Keywords:
Machine learning, Polyunsaturated Fatty Acid (PUFA) metabolites, Heart failure with preserved ejection fraction (HFpEF), Cardiovascular health, Lipidomics framework
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Published
2023-12-15
How to Cite
1.
Faleel D, Elzanaty A, Aradhyula V, Vyas R, Dube P, T. Haller S, Gupta R, J. Kennedy D, J. Khouri S. Machine Learning Analysis of Identifies Polyunsaturated Fatty Acid Metabolites Predictive of Adverse Outcomes In Heart Failure with Preserved Ejection Fraction Patients . Translation [Internet]. 2023 Dec. 15 [cited 2025 Aug. 11];11(3). Available from: http://openjournals.utoledo.edu/index.php/translation/article/view/951
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Section
Dr. Lance D. Dworkin Department of Medicine Research Symposium
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Copyright (c) 2023 Dhilhani Faleel, Ahmed Elzanaty, Vaishnavi Aradhyula, Rohit Vyas, Prabhatchandra Dube, Steven T. Haller, Rajesh Gupta, David J. Kennedy, Samer J. Khouri
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