Smart Applications and Technology for Cardiovascular Disease Management

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 140

Special Issue Editors


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Guest Editor
Department of Cardiology and Angiology, St. Antonius Hospital Gronau GmbH, Möllenweg 22, 48599 Gronau, Germany
Interests: smart technology in cardiology; interventional cardiology; hemodynamics; critical care medicine

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Guest Editor
Department of Cardiology and Intensive Care Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, 32429 Minden, Germany
Interests: smart technology in cardiology; interventional cardiology; electrocardiogram; cardiovascular imaging

Special Issue Information

Dear Colleagues,

Cardiovascular disease (CVD) continues to be a leading cause of morbidity and mortality worldwide, placing a significant burden on healthcare systems and society as a whole. Advancements in technology have opened up new opportunities for innovative approaches in managing CVD, with the emergence of smart applications and technology that have the potential to revolutionize the way we detect, monitor, and treat cardiovascular conditions.

This Special Issue of Bioengineering aims to highlight the latest developments in smart applications and technology for cardiovascular disease management. From wearable devices that enable continuous monitoring of vital signs to artificial intelligence algorithms that predict cardiovascular events, the contributions in this Special Issue will showcase the potential of technology to improve outcomes and quality of life for patients with CVD.

Key topics to be covered in this Special Issue include, but are not limited to, the following:

  • Wearable technology for continuous monitoring of cardiovascular parameters;
  • Mobile applications for self-management and remote monitoring of CVD;
  • Artificial intelligence and machine learning for risk prediction and diagnosis of cardiovascular conditions;
  • Telemedicine and telemonitoring for remote consultation and follow-up care;
  • Virtual reality and simulation tools for training and education in cardiovascular healthcare;
  • Innovative technologies for minimally invasive interventions and surgeries in CVD treatment.

We invite researchers, clinicians, engineers, and industry professionals to contribute original research articles, reviews, and perspectives that address the challenges and opportunities in smart applications and technology for cardiovascular disease management. By bringing together interdisciplinary expertise and cutting-edge innovations in this field, we hope to advance the field of bioengineering and improve outcomes for patients with cardiovascular disease.

Dr. Alexander Samol
Dr. Sven Kaese
Guest Editors

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Keywords

  • cardiovascular disease
  • smart applications
  • technology
  • wearable devices
  • artificial intelligence
  • telemedicine
  • virtual reality

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Published Papers (1 paper)

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Review

16 pages, 680 KiB  
Review
Revolutionizing Utility of Big Data Analytics in Personalized Cardiovascular Healthcare
by Praneel Sharma, Pratyusha Sharma, Kamal Sharma, Vansh Varma, Vansh Patel, Jeel Sarvaiya, Jonsi Tavethia, Shubh Mehta, Anshul Bhadania, Ishan Patel and Komal Shah
Bioengineering 2025, 12(5), 463; https://doi.org/10.3390/bioengineering12050463 - 27 Apr 2025
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Abstract
The term “big data analytics (BDA)” defines the computational techniques to study complex datasets that are too large for common data processing software, encompassing techniques such as data mining (DM), machine learning (ML), and predictive analytics (PA) to find patterns, correlations, and insights [...] Read more.
The term “big data analytics (BDA)” defines the computational techniques to study complex datasets that are too large for common data processing software, encompassing techniques such as data mining (DM), machine learning (ML), and predictive analytics (PA) to find patterns, correlations, and insights in massive datasets. Cardiovascular diseases (CVDs) are attributed to a combination of various risk factors, including sedentary lifestyle, obesity, diabetes, dyslipidaemia, and hypertension. We searched PubMed and published research using the Google and Cochrane search engines to evaluate existing models of BDA that have been used for CVD prediction models. We critically analyse the pitfalls and advantages of various BDA models using artificial intelligence (AI), machine learning (ML), and artificial neural networks (ANN). BDA with the integration of wide-ranging data sources, such as genomic, proteomic, and lifestyle data, could help understand the complex biological mechanisms behind CVD, including risk stratification in risk-exposed individuals. Predictive modelling is proposed to help in the development of personalized medicines, particularly in pharmacogenomics; understanding genetic variation might help to guide drug selection and dosing, with the consequent improvement in patient outcomes. To summarize, incorporating BDA into cardiovascular research and treatment represents a paradigm shift in our approach to CVD prevention, diagnosis, and management. By leveraging the power of big data, researchers and clinicians can gain deeper insights into disease mechanisms, improve patient care, and ultimately reduce the burden of cardiovascular disease on individuals and healthcare systems. Full article
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