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6 articles for “Cardiovascular diseases (CVDs)”
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Leveraging Genome-Wide Association Studies for Precision Medicine in Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) are the leading cause of death globally, with complex etiologies involving genetic, environmental, and lifestyle factors. Genome-wide association studies (GWAS) have significantly advanced the understanding of genetic underpinnings of CVDs by identifying numerous risk loci and variants associated with various cardiovascular conditions. This review explores the potential of GWAS to drive precision medicine in cardiovascular diseases by linking genetic data with clinical outcomes, providing insights into disease …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 35–39 Read article
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Genomic Medicine Revolutionizes Heart Care: A New Standard of Practice
Abstract: The integration of genomic and precision medicine into cardiovascular healthcare represents a transformative advancement in addressing the global burden of cardiovascular diseases (CVDs). Precision medicine leverages genomic, proteomic, and metabolomic data to provide personalized care, optimizing treatment outcomes while minimizing adverse effects. Over the past decade, extensive research has highlighted its potential to revolutionize the management of major CVDs, including myocardial infarction, hypertension, and heart failure, which significantly contribute to …
Published in International Journal of Tropical Medicines · Vol. 2, Issue 2, 2025 · pp. 30–37 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Digital Health Interventions in Cardiovascular Pharmacology: A Review
Abstract: Cardiovascular diseases (CVDs) represent a formidable global health challenge, demanding innovative strategies for timely detection, effective management, and continuous monitoring. This study delves into the transformative potential of digital health interventions (DHIs), such as telemedicine and remote monitoring, in reshaping cardiovascular care paradigms. DHIs offer unparalleled accessibility, convenience, and personalized attention, thereby promising to revolutionize traditional approaches to cardiovascular health management. One of the foremost advantages of DHIs lies in …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 14, Issue 2, 2024 · pp. 1–5 Read article
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Photonic Diagnostics: Harnessing Optical Sensing for Non-Invasive Assessment of Coronary Obstruction
Abstract: Cardiovascular diseases (CVDs) remain the leading cause of mortality globally, with coronary artery blockages primarily atherosclerosis representing a critical challenge. The gold standard for diagnosing coronary artery disease remains invasive coronary angiography, a procedure that, while precise, carries inherent patient risks, high costs, and logistical burdens. Optical sensors, leveraging the principles of light-tissue interaction, offer real-time, high-resolution insights into vascular health, paving the way for early detection of arterial stenoses …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 25–30 Read article
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Understanding Metabolic Syndrome and its Nutritional Management
Abstract: Metabolic syndrome (MetS) is a collection of risk factors, especially when at least three occur together, including abdominal obesity, dyslipidemia, low high-density lipoprotein cholesterol (HDL-c) levels, hypertension, and insulin resistance. MetS is linked to an increased risk of diabetes and cardiovascular diseases (CVDs) if treatment is not received.The causes of MetS include both genetic and acquired factors that contribute to issues such as insulin resistance, chronic low-grade inflammation, and obesity. …
Published in International Journal of Sustainability · Vol. 2, Issue 1, 2025 · pp. 26–37 Read article