Hui Wei^1,2, Zhanfei Ma^1,3,*, Jing Jiang¹, Bisheng Wang¹, Zhong Di¹

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-25, 2026, DOI:10.32604/cmc.2025.069236 - 10 November 2025

Abstract The Internet of Vehicles (IoV) operates in highly dynamic and open network environments and faces serious challenges in secure and real-time authentication and consensus mechanisms. Existing methods often suffer from complex certificate management, inefficient consensus protocols, and poor resilience in high-frequency communication, resulting in high latency, poor scalability, and unstable network performance. To address these issues, this paper proposes a secure and efficient distributed authentication scheme for IoV with reputation-driven consensus and SM9. First, this paper proposes a decentralized authentication architecture that utilizes the certificate-free feature of SM9, enabling lightweight authentication and key negotiation, thereby… More >

Zhuoxi Feng^#,1, Jinyang Liu^#,2, Zihao Wu¹, Ziran Geng¹, Zhimin Liu^1,*

Congenital Heart Disease, Vol.20, No.5, pp. 625-636, 2025, DOI:10.32604/chd.2025.069214 - 30 November 2025

Abstract Congenitally corrected transposition of the great arteries (CCTGA) is a rare congenital heart disease characterized by atrioventricular, ventriculoarterial, and conduction system discordance, commonly accompanied by atrioventricular block (AVB). Pacing in patients with CCTGA and AVB (both pediatric and adult) poses challenges in strategy selection, procedural complexity, and clinical decision-making due to limited evidence. Conventional morphological left ventricular pacing is widely adopted but may induce ventricular dyssynchrony, heart failure, and tricuspid valve dysfunction. While cardiac resynchronization therapy serves as an upgrade for pacing-induced cardiomyopathy and heart failure, its application may be limited by coronary sinus anatomical… More >

Sam Rahimzadeh Holagh¹, Bugao Xu^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2383-2399, 2025, DOI:10.32604/cmes.2025.072259 - 26 November 2025

Abstract Cardiovascular diseases (CVD) remain a leading cause of mortality worldwide, highlighting the need for precise risk assessment tools to support clinical decision-making. This study introduces a meta-learning model for predicting mortality risk in patients with CVD, classifying them into high-risk and low-risk groups. Data were collected from 868 patients at Tabriz Heart Hospital (THH) in Iran, along with two open-access datasets—the Cleveland Heart Disease (CHD) and Faisalabad Institute of Cardiology (FIC) datasets. Data preprocessing involved class balancing via the Synthetic Minority Over-Sampling Technique (SMOTE). Each dataset was then split into training and test sets, and… More >

Soumia Zertal^1,2,*, Asma Saighi^1,2, Sofia Kouah^1,2, Souham Meshoul^3,*, Zakaria Laboudi^2,4

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3737-3782, 2025, DOI:10.32604/cmes.2025.068558 - 30 September 2025

Abstract Cardiovascular diseases (CVDs) continue to present a leading cause of mortality worldwide, emphasizing the importance of early and accurate prediction. Electrocardiogram (ECG) signals, central to cardiac monitoring, have increasingly been integrated with Deep Learning (DL) for real-time prediction of CVDs. However, DL models are prone to performance degradation due to concept drift and to catastrophic forgetting. To address this issue, we propose a real-time CVDs prediction approach, referred to as ADWIN-GFR that combines Convolutional Neural Network (CNN) layers, for spatial feature extraction, with Gated Recurrent Units (GRU), for temporal modeling, alongside adaptive drift detection and… More > Graphic Abstract

Emrah Şişli^1,*, Pelin Köşger²

Congenital Heart Disease, Vol.20, No.4, pp. 531-537, 2025, DOI:10.32604/chd.2025.067271 - 18 September 2025

Abstract Residual atrioventricular valve regurgitation after correction of complete atrioventricular septal defect (cAVSD) is still not ideal. As a modification of the double-patch method, our technique comprises a suture-bite-wide strip of a third patch that is incorporated to the upper margin of the left side of the ventricular septal defect (VSD) patch. This third patch counteracts not only the valvular tissue loss caused by the suture bites but also the rightward displacement of the VSD patch in a bulged fashion that occurs with increased left ventricular pressure after weaning from cardiopulmonary bypass. This unfavorable outcome was More >

Sami Alrabie^#,*, Ahmed Barnawi^#

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2481-2519, 2025, DOI:10.32604/cmes.2025.067977 - 31 August 2025

Abstract In the effort to enhance cardiovascular diagnostics, deep learning-based heart sound classification presents a promising solution. This research introduces a novel preprocessing method: iterative k-means clustering combined with silhouette score analysis, aimed at downsampling. This approach ensures optimal cluster formation and improves data quality for deep learning models. The process involves applying k-means clustering to the dataset, calculating the average silhouette score for each cluster, and selecting the cluster with the highest score. We evaluated this method using 10-fold cross-validation across various transfer learning models from different families and architectures. The evaluation was conducted on… More >

Kamepalli S. L. Prasanna¹, Vijaya J², Parvathaneni Naga Srinivasu¹, Babar Shah³, Farman Ali^4,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1603-1630, 2025, DOI:10.32604/cmc.2025.068707 - 29 August 2025

Abstract Cardiovascular disease prediction is a significant area of research in healthcare management systems (HMS). We will only be able to reduce the number of deaths if we anticipate cardiac problems in advance. The existing heart disease detection systems using machine learning have not yet produced sufficient results due to the reliance on available data. We present Clustered Butterfly Optimization Techniques (RoughK-means+BOA) as a new hybrid method for predicting heart disease. This method comprises two phases: clustering data using Roughk-means (RKM) and data analysis using the butterfly optimization algorithm (BOA). The benchmark dataset from the UCI More >

Tsu-Yang Wu^1,2, Haozhi Wu², Maoxin Tang³, Saru Kumari⁴, Chien-Ming Chen^1,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1715-1732, 2025, DOI:10.32604/cmc.2025.065560 - 29 August 2025

Abstract With the rapid development and widespread adoption of Internet of Things (IoT) technology, the innovative concept of the Internet of Vehicles (IoV) has emerged, ushering in a new era of intelligent transportation. Since vehicles are mobile entities, they move across different domains and need to communicate with the Roadside Unit (RSU) in various regions. However, open environments are highly susceptible to becoming targets for attackers, posing significant risks of malicious attacks. Therefore, it is crucial to design a secure authentication protocol to ensure the security of communication between vehicles and RSUs, particularly in scenarios where More >

Farhan Sarwar¹, Muhammad Shoaib Farooq¹, Nagwan Abdel Samee^2,*, Mona M. Jamjoom³, Imran Ashraf^4,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5897-5914, 2025, DOI:10.32604/cmc.2025.063832 - 30 July 2025

Abstract Environmental transition can potentially influence cardiovascular health. Investigating the relationship between such transition and heart disease has important applications. This study uses federated learning (FL) in this context and investigates the link between climate change and heart disease. The dataset containing environmental, meteorological, and health-related factors like blood sugar, cholesterol, maximum heart rate, fasting ECG, etc., is used with machine learning models to identify hidden patterns and relationships. Algorithms such as federated learning, XGBoost, random forest, support vector classifier, extra tree classifier, k-nearest neighbor, and logistic regression are used. A framework for diagnosing heart disease More >

Mai Ishiwata^1,2, Kohei Ishibashi^1,*, Yoshiaki Kato³, Heima Sakaguchi³, Toshihiro Nakamura¹, Satoshi Oka¹, Yuichiro Miyazaki¹, Akinori Wakamiya¹, Nobuhiko Ueda¹, Kenzaburo Nakajima¹, Tsukasa Kamakura¹, Mitsuru Wada¹, Yuko Inoue¹, Koji Miyamoto¹, Takeshi Aiba¹, Norihiko Takeda², Kengo Kusano¹

Congenital Heart Disease, Vol.20, No.3, pp. 273-286, 2025, DOI:10.32604/chd.2025.067716 - 11 July 2025

Abstract Background: Ventricular arrhythmia is a common cause of mortality in adult congenital heart disease (ACHD). The beneficial effects of implantable cardioverter-defibrillators (ICD) in patients with ACHD have been demonstrated; however, evidence on this topic remains insufficient. This study aimed to assess the long-term outcomes after ICD implantation in the ACHD population. Methods: We retrospectively reviewed 35 consecutive patients with ACHD who underwent ICD implantation between December 2012 and August 2022. ICD implantation was classified as primary or secondary prevention. The long-term outcomes, including all-cause mortality, appropriate and inappropriate ICD therapy, and complications related to ICD implantation, were… More > Graphic Abstract