Coronary heart disease (CHD) is a serious cardiovascular disease (CVD)1that not only has a high mortality rate but also patients are prone to the risk of recurrence even after they are cured and discharged from the hospital, both of which are prognosis-oriented factors for poor outcomes. The...
The most current research demonstrates the various methods used to increase heart disease prediction accuracy. Researchers have made tremendous progress in improving the precision and effectiveness of prediction models through the use of ensemble learning28, feature extraction29, DL models30, and other te...
Cardiovascular risk prediction: basic concepts, current status, and future directions Circulation, 121 (2010), pp. 1768-1777 Google Scholar 21 R.B. D'Agostino, S. Grundy, L.M. Sullivan, P. Wilson CHD Risk Prediction Group Validation of the Framingham coronary heart disease prediction scores: ...
Heart disease prediction by using novel optimization algorithm: A supervised learning prospective 2021, Informatics in Medicine Unlocked Show abstract Risk assessment of coronary heart disease based on cloud-random forest 2023, Artificial Intelligence Review Hybrid stacked ensemble combined with genetic algorit...
Heart failure (HF) after myocardial infarction (MI) is a prevalent disease with a poor prognosis. Relieving pathological cardiac remodeling and preserving cardiac function is a critical link in the treatment of post-MI HF. Thus, more new therapeutic targets are urgently needed. The expression of ...
executive director of Us2.ai; and having a patent for diagnosis and prognosis of chronic heart failure and a patent for automated clinical workflow that recognizes and analyses 2-dimensional and Doppler echo images for cardiac measurements and the diagnosis, prediction and prognosis of heart disease...
highlighted in two reports. Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease, while Part I of the review has focused on studies about myocardial function and risk pred...
Andreas emphasized that nicotine replacement therapies are well-researched and safe even in cardiovascular disease, as shown by a US study that included patients who had sustained a heart attack. A group of the participants was treated with nicotine patches for 10 weeks, while the other group rece...
The present study examines the role of feature selection methods in optimizing machine learning algorithms for predicting heart disease. The Cleveland Heart disease dataset with sixteen feature selection techniques in three categories of filter, wrapper,
Machine learning-based classification of valvular heart disease using cardiovascular risk factors Article Open access 17 October 2024 Analyzing the impact of feature selection methods on machine learning algorithms for heart disease prediction Article Open access 18 December 2023 An active learning mac...