AIMC Topic: Cardiovascular Diseases
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Transfer learning for a tabular-to-image approach: A case study for cardiovascular disease prediction.
Journal of biomedical informatics
Apr 8, 2025
OBJECTIVE: Machine learning (ML) models have been extensively used for tabular data classification but recent works have been developed to transform tabular data into images, aiming to leverage the predictive performance of convolutional neural netwo...
Machine learning integration of multimodal data identifies key features of circulating NT-proBNP in people without cardiovascular diseases.
Scientific reports
Apr 8, 2025
N-Terminal Pro-Brain Natriuretic Peptide (NT-proBNP) is important for diagnosing and predicting heart failure or many other diseases. However, few studies have comprehensively assessed the factors correlated with NT-proBNP levels in people with cardi...
Predicting postoperative complications after pneumonectomy using machine learning: a 10-year study.
Annals of medicine
Apr 7, 2025
BACKGROUND: Reducing postoperative cardiovascular and neurological complications (PCNC) during thoracic surgery is the key to improving postoperative survival.
Predator crow search optimization with explainable AI for cardiac vascular disease classification.
Scientific reports
Apr 5, 2025
The proposed framework optimizes Explainable AI parameters, combining Predator crow search optimization to refine the predictive model's performance. To prevent overfitting and enhance feature selection, an information acquisition-based technique is ...
Implementation of a national AI technology program on cardiovascular outcomes and the health system.
Nature medicine
Apr 4, 2025
Coronary artery disease (CAD) is a major cause of ill health and death worldwide. Coronary computed tomographic angiography (CCTA) is the first-line investigation to detect CAD in symptomatic patients. This diagnostic approach risks greater second-li...
Responsible CVD screening with a blockchain assisted chatbot powered by explainable AI.
Scientific reports
Apr 4, 2025
Cardiovascular disease (CVD) is rising as a significant concern for the healthcare sector around the world. Researchers have applied multiple traditional approaches to making healthcare systems find new solutions for the CVD concern. Artificial Intel...
Can small dense LDL cholesterol be estimated from the lipid profile?
Current opinion in lipidology
Apr 3, 2025
PURPOSE OF REVIEW: Small dense low-density lipoprotein cholesterol (sdLDL-C) is recognized for its strong atherosclerogenic potential. However, its direct measurement remains impractical in clinical settings due to its high cost, time constraints, an...
A domain adaptation model for carotid ultrasound: Image harmonization, noise reduction, and impact on cardiovascular risk markers.
Computers in biology and medicine
Apr 3, 2025
Deep learning has been used extensively for medical image analysis applications, assuming the training and test data adhere to the same probability distributions. However, a common challenge arises when dealing with medical images generated by differ...
Machine learning and multi-omics integration: advancing cardiovascular translational research and clinical practice.
Journal of translational medicine
Apr 2, 2025
The global burden of cardiovascular diseases continues to rise, making their prevention, diagnosis and treatment increasingly critical. With advancements and breakthroughs in omics technologies such as high-throughput sequencing, multi-omics approach...
Improved prediction and risk stratification of major adverse cardiovascular events using an explainable machine learning approach combining plasma biomarkers and traditional risk factors.
Cardiovascular diabetology
Apr 2, 2025
BACKGROUND: Cardiovascular diseases (CVD) remain the leading cause of morbidity and mortality globally. Traditional risk models, primarily based on established risk factors, often lack the precision needed to accurately predict new-onset major advers...
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