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12 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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Predicting Cardiovascular Disease Risk Using Machine Learning: A Comprehensive Review
Abstract: Cardiovascular diseases (CVDs) are the prevalent morbid and fatal conditions worldwide. Repetition is key to stopping these diseases before they start and before they appear. With the advancement of data analytics and AI, machine learning (ML) has emerged as a powerful tool for predicting CVD risk and delivering personalized healthcare solutions. This review comprehensively summarizes the latest trends in the use of machine learning techniques to predict cardiovascular disease risk. …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 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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Patient Teaching for Cardiac Rehabilitation in Cardio Diabetes
Abstract: Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, and are a significant contributor to morbidity and health-related costs. Coronary artery disease (CAD)—the most common type of CVDs—is considered as a chronic condition and, therefore, requires a careful medical management with multiple recommendations for patients to achieve optimal secondary prevention. As a consequence, patient education is a necessary step to promote patient understanding of the recommended therapies and behavior …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 7, Issue 2, 2017 · pp. 29–35 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
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A Systematic Review for Heart Disease Prediction Using AIML Algorithms
Abstract: Cardiovascular diseases (CVDs), commonly known as heart diseases, have consistently held the position of being the primary global cause of mortality for many years. They are also the most serious illness in India and the rest of the world. So, a method that is reliable, accurate, and easy to use is needed to find these diseases early and start the right treatment. Using a variety of medical datasets, machine learning …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 53–61 Read article
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Detection of Cardiovascular Disease using AI and ML: A Review
Abstract: In the 21st century according to statistics, the risk of cardiovascular disease has become more common and the death rate caused by it is increasing way more. Around 17.9 million lives are taken by CVDs each year. There are various reasons causing it but most importantly it is caused by not identifying it, hence it becomes a very important task for the human race to identify the CVDs and deal …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 11–21 Read article
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Heart Disease Prediction Using ANN Based Ensemble Framework (ANNEF) Approach
Abstract: The heart is the most important organ in the human body. One of the deadliest illnesses, heart disease is to blame for countless deaths worldwide. Because of the formation of fatty plaques in arteries, the heart fails to supply enough blood to other body areas to carry out its usual functions in heart disease (atherosclerosis). Age, a sedentary lifestyle, a family history of heart disease, stress, and other factors are …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 3, 2022 · pp. 38–45 Read article
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Assessment of Total Cardiovascular Risk using WHO/ISH Risk Prediction Charts in Chaman Colony, Dhanas, Chandigarh in India
Abstract: Background: Cardiovascular diseases (CVD), largely heart disease and stroke, accounts for almost half of all NCD-related deaths and is now the leading cause of death in low- and middle-income countries (LMIC). There are several risk factors which are responsible for developing CVDs. Many of the risk factors such as smoking, hypertension, dyslipidaemia, diabetes, physical inactivity and obesity are potentially modifiable by health counselling. Cardiovascular diseases are preventable so accurate estimation …
Published in Research and Reviews: A Journal of Medicine · Vol. 7, Issue 2, 2017 · pp. 1–6 Read article