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Life
Special Issues
Comprehensive Treatment and Precision Medicine Strategies for Heart Disease
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Comprehensive Treatment and Precision Medicine Strategies for Heart Disease

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Medical Research".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 914

Special Issue Editor

Dr. Serge Sicouri

E-Mail Website
Guest Editor
1. Department of Cardiac Surgery Research, Lankenau Institute for Medical Research, Main Line Health, Wynnewood, PA 19096 USA
2. Department of Cardiac Surgery, Lankenau Heart Institute, Main Line Health, Wynnewood, PA 19096 USA
Interests: cardiac surgery; arrhythmias; clinical cardiology; electrophysiology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue, “Comprehensive Treatment and Precision Medicine Strategies for Heart Disease,” aims to bring together original research, systematic reviews, and expert perspectives on the evolving landscape of cardiovascular science.     With the growing integration of artificial intelligence, advanced imaging, molecular diagnostics, and tailored approaches, heart disease management is entering a new era of precision medicine.

We welcome contributions that explore strategies across prevention and diagnosis of complex cardiac conditions. Topics of interest include novel risk prediction models, individualized treatment pathways, AI-driven decision support, and translational research that bridges bench discoveries with bedside applications.

By highlighting state-of-the-art therapies and forward-looking innovations, this Special Issue will provide a platform for researchers to share insights that can shape future standards in cardiovascular medicine.

Dr. Serge Sicouri
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Life is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • precision medicine
  • artificial intelligence
  • risk stratification
  • machine learning
  • translational research
  • cardiovascular outcomes

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Published Papers (1 paper)

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Review

25 pages, 1951 KB  
Review
Artificial Intelligence–Driven Hypertension Management: Implications for Quality Improvement and Prevention of End-Organ Damage
by Laura Ramlawi, Serge Sicouri, Vasiliki Androutsopoulou, Massimo Baudo, Andrew Xanthopoulos, Alexandra Bekiaridou and Dimitrios E. Magouliotis
Life 2026, 16(4), 573; https://doi.org/10.3390/life16040573 - 1 Apr 2026
Viewed by 666
Abstract
Hypertension remains a leading modifiable risk factor for cardiovascular morbidity and mortality. Nonetheless, blood pressure control rates remain suboptimal despite established treatment guidelines and effective pharmacologic therapies. In parallel, artificial intelligence (AI) has rapidly expanded within cardiovascular medicine, demonstrating promising capabilities in disease [...] Read more.
Hypertension remains a leading modifiable risk factor for cardiovascular morbidity and mortality. Nonetheless, blood pressure control rates remain suboptimal despite established treatment guidelines and effective pharmacologic therapies. In parallel, artificial intelligence (AI) has rapidly expanded within cardiovascular medicine, demonstrating promising capabilities in disease detection, risk prediction, and clinical decision support. However, most AI applications in hypertension have focused primarily on algorithmic performance rather than real-world implementation or measurable improvements in patient outcomes. This review examines artificial intelligence-driven hypertension management through the lens of quality improvement and prevention of end-organ damage. We summarize current applications of machine learning, deep learning, natural language processing, and imaging analytics in hypertension detection and risk stratification, and critically evaluate their integration into clinical workflows. Particular emphasis is placed on therapeutic inertia, primary care-centered implementation, and the use of AI to support continuous quality improvement frameworks. Beyond blood pressure reduction alone, we explore the potential of AI to identify patients at risk for hypertensive heart disease, heart failure, aortic pathology, renal dysfunction, and cerebrovascular events. We discuss implementation challenges, including external validation, algorithmic bias, workflow integration, and regulatory considerations, which must be addressed to ensure safe and equitable deployment. Artificial intelligence offers the opportunity to transform hypertension management from reactive blood pressure control to proactive organ protection. Critically, AI-driven quality improvement interventions must be evaluated against established non-AI strategies, including pharmacist-led management and team-based care, which provide the benchmarks for demonstrating added clinical value. Achieving this shift will require embedding predictive analytics within structured, outcome-oriented systems of care and rigorously evaluating their impact on cardiovascular morbidity and mortality. Full article
(This article belongs to the Special Issue Comprehensive Treatment and Precision Medicine Strategies for Heart Disease)
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