Tsu-Yang Wu^1,2,3, Haozhi Wu³, Maoxin Tang^1,2, Saru Kumari⁴, Chien-Ming Chen^1,2,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3175-3192, 2025, DOI:10.32604/cmc.2025.065717 - 03 July 2025

Abstract As a model for the next generation of the Internet, the metaverse—a fully immersive, hyper-temporal virtual shared space—is transitioning from imagination to reality. At present, the metaverse has been widely applied in a variety of fields, including education, social entertainment, Internet of vehicles (IoV), healthcare, and virtual tours. In IoVs, researchers primarily focus on using the metaverse to improve the traffic safety of vehicles, while paying limited attention to passengers’ social needs. At the same time, Social Internet of Vehicles (SIoV) introduces the concept of social networks in IoV to provide better resources and services… More >

Deepak Mahto¹, Sudhakar Kumar¹, Sunil K. Singh¹, Amit Chhabra¹, Irfan Ahmad Khan², Varsha Arya^3,4, Wadee Alhalabi⁵, Brij B. Gupta^6,7,8,9,*, Bassma Saleh Alsulami¹⁰

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3743-3767, 2025, DOI:10.32604/cmes.2025.063427 - 30 June 2025

Abstract Cardiovascular diseases (CVDs) remain one of the foremost causes of death globally; hence, the need for several must-have, advanced automated diagnostic solutions towards early detection and intervention. Traditional auscultation of cardiovascular sounds is heavily reliant on clinical expertise and subject to high variability. To counter this limitation, this study proposes an AI-driven classification system for cardiovascular sounds whereby deep learning techniques are engaged to automate the detection of an abnormal heartbeat. We employ FastAI vision-learner-based convolutional neural networks (CNNs) that include ResNet, DenseNet, VGG, ConvNeXt, SqueezeNet, and AlexNet to classify heart sound recordings. Instead of… More >

Siarhei A. Dabravolski^1,*, Michael I. Bukrinsky², Aleksandra S. Utkina³, Alessio L. Ravani⁴, Vasily N. Sukhorukov^5,6, Alexander N. Orekhov⁷

BIOCELL, Vol.49, No.6, pp. 931-959, 2025, DOI:10.32604/biocell.2025.062789 - 24 June 2025

Abstract Neutrophil extracellular traps (NET) have emerged as critical players in the pathogenesis of atherosclerosis and other cardiovascular diseases (CVD). These web-like structures, composed of DNA, histones, and granule proteins released by neutrophils, contribute significantly to both inflammation and thrombosis. This manuscript offers a comprehensive review of the recent literature on the involvement of NET in atherosclerosis, highlighting their interactions with various pathophysiological processes and their potential as biomarkers for CVD. Notably, the impact of radiation on NET formation is explored, emphasising how oxidative stress and inflammatory responses drive NET release, contributing to plaque instability. The… More >

Amrutanshu Panigrahi¹, Abhilash Pati¹, Bibhuprasad Sahu², Ashis Kumar Pati³, Subrata Chowdhury⁴, Khursheed Aurangzeb^5,*, Nadeem Javaid⁶, Sheraz Aslam^7,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1633-1657, 2025, DOI:10.32604/cmc.2025.063562 - 09 June 2025

Abstract The integration of IoT and Deep Learning (DL) has significantly advanced real-time health monitoring and predictive maintenance in prognostic and health management (PHM). Electrocardiograms (ECGs) are widely used for cardiovascular disease (CVD) diagnosis, but fluctuating signal patterns make classification challenging. Computer-assisted automated diagnostic tools that enhance ECG signal categorization using sophisticated algorithms and machine learning are helping healthcare practitioners manage greater patient populations. With this motivation, the study proposes a DL framework leveraging the PTB-XL ECG dataset to improve CVD diagnosis. Deep Transfer Learning (DTL) techniques extract features, followed by feature fusion to eliminate redundancy… More >

Chih-Ta Yen^1,*, Jung-Ren Wong², Chia-Hsang Chang²

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 347-363, 2025, DOI:10.32604/cmc.2025.063389 - 09 June 2025

Abstract In its 2023 global health statistics, the World Health Organization noted that noncommunicable diseases (NCDs) remain the leading cause of disease burden worldwide, with cardiovascular diseases (CVDs) resulting in more deaths than the three other major NCDs combined. In this study, we developed a method that can comprehensively detect which CVDs are present in a patient. Specifically, we propose a multi-label classification method that utilizes photoplethysmography (PPG) signals and physiological characteristics from public datasets to classify four types of CVDs and related conditions: hypertension, diabetes, cerebral infarction, and cerebrovascular disease. Our approach to multi-disease classification… More >

Isha Kiran¹, Shahzad Ali^2,3, Sajawal ur Rehman Khan^4,5, Musaed Alhussein⁶, Sheraz Aslam^7,8,*, Khursheed Aurangzeb^6,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5057-5078, 2025, DOI:10.32604/cmc.2025.058724 - 06 March 2025

Abstract Cardiovascular disease (CVD) remains a leading global health challenge due to its high mortality rate and the complexity of early diagnosis, driven by risk factors such as hypertension, high cholesterol, and irregular pulse rates. Traditional diagnostic methods often struggle with the nuanced interplay of these risk factors, making early detection difficult. In this research, we propose a novel artificial intelligence-enabled (AI-enabled) framework for CVD risk prediction that integrates machine learning (ML) with eXplainable AI (XAI) to provide both high-accuracy predictions and transparent, interpretable insights. Compared to existing studies that typically focus on either optimizing ML… More >

Ali Alqarni^*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 389-406, 2025, DOI:10.32604/cmc.2024.059238 - 03 January 2025

Abstract Open networks and heterogeneous services in the Internet of Vehicles (IoV) can lead to security and privacy challenges. One key requirement for such systems is the preservation of user privacy, ensuring a seamless experience in driving, navigation, and communication. These privacy needs are influenced by various factors, such as data collected at different intervals, trip durations, and user interactions. To address this, the paper proposes a Support Vector Machine (SVM) model designed to process large amounts of aggregated data and recommend privacy-preserving measures. The model analyzes data based on user demands and interactions with service More >

A. Robert Singh¹, Suganya Athisayamani², Gyanendra Prasad Joshi³, Bhanu Shrestha^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 299-327, 2025, DOI:10.32604/cmes.2024.055599 - 17 December 2024

Abstract Myocardial perfusion imaging (MPI), which uses single-photon emission computed tomography (SPECT), is a well-known estimating tool for medical diagnosis, employing the classification of images to show situations in coronary artery disease (CAD). The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks (CNNs). This paper uses a SPECT classification framework with three steps: 1) Image denoising, 2) Attenuation correction, and 3) Image classification. Image denoising is done by a U-Net architecture that ensures effective image denoising. Attenuation correction is implemented by a convolution neural network model that… More >

E. David Crawford¹, David Albala², Marc B. Garnick³, Andrew W. Hahn⁴, Paul Maroni⁵, Rana R. McKay⁶, Martin Miner⁷, Peter Orio III⁸, Kshitij Pandit¹, Scott Sellinger⁹, Evan Y. Yu¹⁰, Robert H. Eckel¹¹

Canadian Journal of Urology, Vol.31, No.2, pp. 11820-11825, 2024

Abstract Introduction: Risk of cardiovascular disease is higher among men with prostate cancer than men without, and prostate cancer treatments (especially those that are hormonally based) are associated with increased cardiovascular risk.
Materials and methods: An 11-member panel of urologic, medical, and radiation oncologists (along with a men’s health specialist and an endocrinologist/ preventive cardiologist) met to discuss current practices and challenges in the management of cardiovascular risk in prostate cancer patients who are taking androgen deprivation therapies (ADT) including LHRH analogues, alone and in combination with androgen-targeted therapies (ATTs).
Results: The panel developed an assessment algorithm to categorize… More >

Edo Bedzra^1,*, Eli Contorno², Herra Javed², Amna Qasim³, James St. Louis⁴, Taufiek Konrad Rajab²

Congenital Heart Disease, Vol.19, No.6, pp. 541-562, 2024, DOI:10.32604/chd.2025.059788 - 27 January 2025

Abstract Since the first identification of Tetralogy of Fallot in 1671, consisting of a combination of anatomical defects including biventricular origin of the aorta, maligned ventricular septal defect, overriding aorta, and narrowing or atresia of the pulmonary outflow tract. The first successful operation consisted of a shunt between the left subclavian artery and pulmonary artery. Following this palliative procedure, complete repair is performed once the patient reaches indicative criteria. Since the first attempts at surgical palliation and repair, techniques and outcomes have improved drastically. Definitive repair of Tetralogy of Fallot consists of a multi-patch closure of More >