AIMC Topic: Cardiovascular Diseases
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Non-redundant association rules between diseases and medications: an automated method for knowledge base construction.
BMC medical informatics and decision making
Apr 15, 2015
BACKGROUND: The widespread use of electronic health records (EHRs) has generated massive clinical data storage. Association rules mining is a feasible technique to convert this large amount of data into usable knowledge for clinical decision making, ...
A novel neural-inspired learning algorithm with application to clinical risk prediction.
Journal of biomedical informatics
Jan 6, 2015
Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for...
Innovative application of confocal Raman spectroscopy and Machine learning in cardiovascular diseases identification.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Nov 5, 2025
Myocardial hypertrophy and heart failure are leading causes of mortality in cardiovascular diseases, yet current diagnostic techniques lack the resolution to monitor molecular changes effectively. In this study, we employed confocal Raman spectroscop...
The Impact of Social Determinants on Cardiovascular Mortality: A Zip Code-Level Analysis in Indiana.
Studies in health technology and informatics
Aug 7, 2025
Cardiovascular disease (CVD) is the leading cause of death globally and is expected to become the top global cause of death by 2030. Although the role of social determinants of health (SDoH) in CVD outcomes is well-established, integrating these fact...
AI Bias and Confounding Risk in Health Feature Engineering for Machine Learning Classification Task.
Studies in health technology and informatics
Aug 7, 2025
Recent advancements in machine learning bring unique opportunities in health fields but also pose considerable challenges. Due to stringent ethical considerations and resource constraints, health data can vary in scope, population coverage, and colle...
[Artificial intelligence for randomized controlled trials in cardiology: applications and future perspectives].
Giornale italiano di cardiologia (2006)
Aug 1, 2025
Integrating artificial intelligence (AI) into cardiovascular clinical trials is emerging as a key factor in streamlining patient selection, data collection, endpoint monitoring, and outcome analysis. On the one hand, machine learning and deep learnin...
Personalized medicine for cardiovascular diseases: how next generation epigenetic technologies can contribute?
Epigenomics
Jul 1, 2025
Advances in DNA methylation and artificial intelligence have led to new methods for assessing risk and diagnosing coronary heart disease (CHD), the leading cause of death. However, whether these technologies can also be harnessed to generate new phar...
Integration of metabolomics and machine learning for precise management and prevention of cardiometabolic risk in Asians.
Clinical nutrition (Edinburgh, Scotland)
Jul 1, 2025
Rapid changes in dietary patterns have led to a rise in cardiometabolic diseases (CMDs) worldwide, highlighting the urgent need for effective dietary strategies to address the health issues. Compared to Caucasians, Asians are more susceptible to CMDs...
Development of a machine learning model for predicting cardiovascular risk factors and major adverse cardiovascular events in young adults with glucose metabolism disorders.
Medicina clinica
Jun 13, 2025
BACKGROUND: Glucose metabolism disorders (GMDs) are a serious global public health issue, characterized by a high incidence rate and youthfulness. GMDs contribute to the occurrence of major adverse cardiovascular events (MACEs), meanwhile with the re...
Hybrid time series and machine learning models for forecasting cardiovascular mortality in India: an age specific analysis.
BMC public health
Jun 10, 2025
Cardiovascular disease (CVD) is a primary cause of death in India, accounting for a significant portion of the global CVD burden. This study looks at statistics on heart disease mortality from the Institute for Health Metrics and Evaluation (IHME) fr...
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