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
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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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How to Cite
1.
Machine Learning Analysis of Identifies Polyunsaturated Fatty Acid Metabolites Predictive of Adverse Outcomes In Heart Failure with Preserved Ejection Fraction Patients . Translation. 2023;11(3). doi:10.46570/utjms.vol11-2023-951
