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Heart Diseases

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[The development of model of prognostication and minimization of risk of by-effects under combined application of agents for treatment of chronic cardiac deficiency using AI].

Problemy sotsial'noi gigieny, zdravookhraneniia i istorii meditsiny
The chronic cardiac deficiency continues to be one of the leading health care problems requiring innovative solutions. The article presents mathematical algorithm to evaluate drug interactions and targeted to minimize side effects and to optimize chr...

A hybrid approach with metaheuristic optimization and random forest in improving heart disease prediction.

Scientific reports
Cardiovascular diseases (CVD)  a major cause of morbidity and mortality among the world's non-communicable disease incidences. Though these practices are in use for diagnostics of different CVDs in clinical settings, need improvement because they are...

Construction and validation of a predictive model for intracardiac thrombus risk in patients with dilated cardiomyopathy: a retrospective study.

BMC cardiovascular disorders
BACKGROUND: Systemic embolic events due to exfoliation of intracardiac thrombus (ICT) are one of the catastrophic complications of dilated cardiomyopathy (DCM). This study intended to develop a prediction model to predict the risk of ICT in patients ...

Optimizing stability of heart disease prediction across imbalanced learning with interpretable Grow Network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Heart disease prediction models often face stability challenges when applied to public datasets due to significant class imbalances, unlike the more balanced benchmark datasets. These imbalances can adversely affect various...

Optimized machine learning mechanism for big data healthcare system to predict disease risk factor.

Scientific reports
Heart disease is becoming more and more common in modern society because of factors like stress, inadequate diets, etc. Early identification of heart disease risk factors is essential as it allows for treatment plans that may reduce the risk of sever...

Ensemble learning with explainable AI for improved heart disease prediction based on multiple datasets.

Scientific reports
Heart disease is one of the leading causes of death worldwide. Predicting and detecting heart disease early is crucial, as it allows medical professionals to take appropriate and necessary actions at earlier stages. Healthcare professionals can diagn...

Comparative analysis of heart disease prediction using logistic regression, SVM, KNN, and random forest with cross-validation for improved accuracy.

Scientific reports
This primary research paper emphasizes cross-validation, where data samples are reshuffled in each iteration to form randomized subsets divided into n folds. This method improves model performance and achieves higher accuracy than the baseline model....

Free-breathing, Highly Accelerated, Single-beat, Multisection Cardiac Cine MRI with Generative Artificial Intelligence.

Radiology. Cardiothoracic imaging
Purpose To develop and evaluate a free-breathing, highly accelerated, multisection, single-beat cine sequence for cardiac MRI. Materials and Methods This prospective study, conducted from July 2022 to December 2023, included participants with various...

IoT driven smart health monitoring for heart disease prediction using quantum kernel enhanced sardine diffusion and CNN.

Scientific reports
Heart disease is one of the major causes of death worldwide, and the traditional diagnostic procedures typically cause delays in treatment, particularly in low-resource regions. In this article, we propose a novel IoT-based Quantum Kernel-Enhanced Sa...