Vijay Nambi

Dec 5, 2024 | digitalcommons.library.tmc.edu | Byron C. Jaeger |Matthew W. Segar |Kershaw V. Patel |Vijay Nambi

BACKGROUND: Heart failure (HF) risk and the underlying risk factors vary by race. Traditional models for HF risk prediction treat race as a covariate in risk prediction and do not account for significant parameters such as cardiac biomarkers. Machine learning (ML) may offer advantages over traditional modeling techniques to develop race-specific HF risk prediction models and to elucidate important contributors of HF development across races.

Dec 5, 2024 | digitalcommons.library.tmc.edu | Aliza Hussain |Caroline Sun |Elizabeth Selvin |Vijay Nambi

AIMS: Despite statin and antihypertensive therapies, older Americans have high atherosclerotic cardiovascular disease (ASCVD) risk. Novel measures of triglyceride-rich lipoproteins, low-density lipoprotein triglycerides (LDL-TG), and remnant-like particle cholesterol (RLP-C), are associated with ASCVD in middle-aged adults.

Nov 12, 2024 | researchgate.net | Mahmoud Al Rifai |Michael Blaha |Vijay Nambi

To read the full-text of this research, you can request a copy directly from the authors. ResearchGate has not been able to resolve any citations for this publication. ResearchGate has not been able to resolve any references for this publication. ArticleFull-text availableOctober 2024 · BiosensorsSheikh Muhammad Asher Iqbal Mary Ann LeavittImadeldin Mahgoub[...] Waseem AsgharCardiovascular diseases are a leading cause of death worldwide.