Chunlai Du^1,#, Xin Gu^1,#, Yanhui Guo^2,*, Siqi Guo³, Ziwei Pang³, Yi Du³, Guoqing Du^3,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3435-3450, 2025, DOI:10.32604/cmc.2025.060212 - 16 April 2025

Abstract Coronary artery disease is a highly lethal cardiovascular condition, making early diagnosis crucial for patients. Echocardiograph is employed to identify coronary heart disease (CHD). However, due to issues such as fuzzy object boundaries, complex tissue structures, and motion artifacts in ultrasound images, it is challenging to detect CHD accurately. This paper proposes an improved Transformer model based on the Feedback Self-Attention Mechanism (FSAM) for classification of ultrasound images. The model enhances attention weights, making it easier to capture complex features. Experimental results show that the proposed method achieves high levels of accuracy, recall, precision, F1 More >

Iman S. Al-Mahdi¹, Saad M. Darwish^1,*, Magda M. Madbouly²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 875-909, 2025, DOI:10.32604/cmes.2025.061623 - 11 April 2025

Abstract Heart disease prediction is a critical issue in healthcare, where accurate early diagnosis can save lives and reduce healthcare costs. The problem is inherently complex due to the high dimensionality of medical data, irrelevant or redundant features, and the variability in risk factors such as age, lifestyle, and medical history. These challenges often lead to inefficient and less accurate models. Traditional prediction methodologies face limitations in effectively handling large feature sets and optimizing classification performance, which can result in overfitting poor generalization, and high computational cost. This work proposes a novel classification model for heart… More >

Vatche Bahudian, John Valdovinos^*

Congenital Heart Disease, Vol.20, No.1, pp. 115-127, 2025, DOI:10.32604/chd.2025.063991 - 18 March 2025

Abstract Background: The population of Fontan patients, patients born with a single functioning ventricle, is growing. There is a growing need to develop algorithms for this population that can predict health outcomes. Artificial intelligence models predicting short-term and long-term health outcomes for patients with the Fontan circulation are needed. Generative adversarial networks (GANs) provide a solution for generating realistic and useful synthetic data that can be used to train such models. Methods: Despite their promise, GANs have not been widely adopted in the congenital heart disease research community due, in some part, to a lack of knowledge… More >

Roberto Noya Galluzzo¹, Karine Souza Da Correggio¹, Aldo von Wangenheim², Heron Werner³, Nathalie Jeanne Bravo-Valenzuela⁴, Edward Araujo Júnior^5,6,*, Alexandre Sherlley Casimiro Onofre⁷

Congenital Heart Disease, Vol.20, No.1, pp. 89-101, 2025, DOI:10.32604/chd.2025.063014 - 18 March 2025

Abstract Introduction: Diabetes mellitus (DM), a metabolic disorder, leads to organ damage due to chronic hyperglycemia with multiple pathogenic processes. Gestational diabetes mellitus (GDM) poses risks to mothers and offspring, increasing the incidence of structural congenital heart disease (CHD) and myocardial hypertrophy in newborns. Objective: This review aimed to examine the association between maternal diabetes mellitus and CHD. Methods: This systematic review used the STROBE and TRIPOD checklists registered in PROSPERO (CRD42024513858). It focused on diagnostic test accuracy using the Munn et al. protocol for systematic assessment, emphasizing the “PIRD”: Population, Index Test, Reference Test, Diagnosis of Interest.… More >

John J. Araujo^1,2,*

Congenital Heart Disease, Vol.20, No.1, pp. 61-75, 2025, DOI:10.32604/chd.2025.062927 - 18 March 2025

Abstract Today, more than 90% of children who are born with congenital heart disease survive and reach adulthood, especially in developed countries. Consequently, the population of adults with congenital heart disease has increased significantly over the last few decades. In Latin America and the Caribbean countries, this same scenario is occurring at an accelerated pace. Loss to follow-up is a global problem in adults with congenital heart disease, ranging from 30–60%. In Latin America and Caribbean countries, it is estimated that less than 10% of adults with congenital heart disease are being followed. The small number More >

Ruhul Amin¹, Md. Jamil Khan¹, Tonway Deb Nath¹, Md. Shamim Reza², Jungpil Shin^3,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3907-3919, 2025, DOI:10.32604/cmc.2025.061645 - 06 March 2025

Abstract Heart disease includes a multiplicity of medical conditions that affect the structure, blood vessels, and general operation of the heart. Numerous researchers have made progress in correcting and predicting early heart disease, but more remains to be accomplished. The diagnostic accuracy of many current studies is inadequate due to the attempt to predict patients with heart disease using traditional approaches. By using data fusion from several regions of the country, we intend to increase the accuracy of heart disease prediction. A statistical approach that promotes insights triggered by feature interactions to reveal the intricate pattern… More >

Kassymbek Ozhikenov¹, Zhadyra Alimbayeva^1,*, Chingiz Alimbayev^1,2,*, Aiman Ozhikenova¹, Yeldos Altay¹

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5257-5284, 2025, DOI:10.32604/cmc.2025.061508 - 06 March 2025

Abstract Myocardial infarction (MI) is one of the leading causes of death globally among cardiovascular diseases, necessitating modern and accurate diagnostics for cardiac patient conditions. Among the available functional diagnostic methods, electrocardiography (ECG) is particularly well-known for its ability to detect MI. However, confirming its accuracy—particularly in identifying the localization of myocardial damage—often presents challenges in practice. This study, therefore, proposes a new approach based on machine learning models for the analysis of 12-lead ECG data to accurately identify the localization of MI. In particular, the learning vector quantization (LVQ) algorithm was applied, considering the contribution… More >

Ethan Katznelson¹, Matthew J. Navarro², Su Yuan¹, Dhurv S. Kazi³, Harsimran S. Singh^1,*

Congenital Heart Disease, Vol.19, No.6, pp. 627-634, 2024, DOI:10.32604/chd.2025.062309 - 27 January 2025

Abstract Congenital Heart Disease (CHD) is the most common birth defect and a leading cause of infant morbidity and mortality worldwide. While genetic factors play a significant role in its development, up to 30% of CHD is associated with modifiable risk factors and external maternal exposures. Climate change, driven by increased atmospheric pollutants from fossil fuel combustion, leads to rising global temperatures and worsening air quality, which pose emerging threats to maternal and fetal health. This review explores the mechanisms by which environmental factors associated with climate change, specifically extreme heat and air pollution, may influence… More >

Manouk H. C. Linderhof^1,#, Hoang H. Nguyen^1,2,#, Annemien E. van den Bosch¹, Mathijs S. van Schie¹, Vehpi Yildirim¹, Yannick J. H. J. Taverne³, Natasja M. S. de Groot^1,*

Congenital Heart Disease, Vol.19, No.6, pp. 577-592, 2024, DOI:10.32604/chd.2025.062129 - 27 January 2025

Abstract Surgical ablation (SA) has become an essential rhythm-control strategy for managing tachyarrhythmias in patients with congenital heart disease. Atrial tachyarrhythmias, such as atrial flutter and atrial fibrillation, are prevalent in congenital heart disease, affecting up to 50% of patients, and pose significant risks, including increased morbidity and mortality. Ventricular tachyarrhythmias, though less common, can lead to sudden cardiac death, particularly in conditions like Tetralogy of Fallot. Prior studies suggested that SA for tachyarrhythmias in patients with congenital heart disease offers significant benefits, including superior long-term rhythm control compared to catheter ablation (CA). Atrial tachyarrhythmia burden… More > Graphic Abstract

Xiaofeng Wang^#, Chenyu Li^#, Xia Li, Zhongyuan Lu, Xu Wang^*

Congenital Heart Disease, Vol.19, No.6, pp. 617-626, 2024, DOI:10.32604/chd.2025.058712 - 27 January 2025

Abstract Objectives: Fluid overload is common after congenital cardiac surgeries. This requires early application of peritoneal dialysis (PD) in infants to improve surgical outcomes. The objective of this study is to ascertain the factors correlated with the necessity for PD in infants, thereby informing the prophylactic placement of PD catheters intraoperatively. Methods: This was a single-center retrospective study. Infants aged three months or younger who underwent congenital cardiac procedures at the Fuwai Hospital between 2021 and 2022 were included. Patients with chronic renal failure or without RACHS-1 categories were excluded. Based on whether postoperative PD treatment… More >