Digital Precision Health Management of Cardiovascular and Cerebrovascular Diseases

Dear Colleagues,

Cardiovascular and cerebrovascular diseases (CVDs) remain the leading causes of mortality and long-term disability worldwide, imposing an unsustainable burden on healthcare systems and societies. Despite decades of advances in pharmacological and interventional therapies, substantial gaps persist in early risk stratification, real-time disease monitoring, treatment individualization, and post-acute care coordination. The convergence of digital technologies—wearable sensors, artificial intelligence (AI), cloud computing, and mobile health (mHealth) platforms—with precision medicine paradigms offers a transformative opportunity to close these gaps. This Special Issue, “Digital Precision Health Management of Cardiovascular and Cerebrovascular Diseases”, aims to showcase cutting-edge research that harnesses digital tools to deliver the right intervention to the right patient at the right time, across the entire disease continuum from primary prevention to rehabilitation.

Traditional risk scores, while useful, rely on static snapshots and population-averaged estimates, often missing the dynamic, heterogeneous nature of vascular pathology. Digital phenotyping, enabled by continuous physiological monitoring (e.g., photoplethysmography, electrocardiogram, accelerometry, and continuous glucose monitoring), now generates high-dimensional, time-stamped data streams that capture day-to-day variability in blood pressure, heart rhythm, physical activity, sleep quality, and glycaemic control. When integrated with electronic health records, genomic profiles, and environmental exposures, these big data become the fuel for machine learning algorithms that can uncover novel endotypes, predict imminent events (e.g., atrial fibrillation, stroke, or acute coronary syndrome) with unprecedented temporal precision, and adaptively recalibrate risk as clinical status evolves.

Equally critical is the management of chronic phases. Digital therapeutic platforms—incorporating interactive coaching, cognitive behavioural therapy modules, and gamified exercise regimens—have demonstrated efficacy in improving medication adherence, dietary modification, and physical rehabilitation, particularly when tailored to patients’ cognitive capacities, cultural contexts, and daily routines. Remote patient monitoring programmes, using implantable or patch-based sensors, have reduced hospital readmissions for heart failure and post-stroke complications by enabling early detection of decompensation and timely tele-consultation. However, the scalability, interoperability, and clinical validation of these digital solutions remain uneven, and evidence on long-term outcomes, cost-effectiveness, and health equity is urgently needed.

This Special Issue invites original research, systematic reviews, meta-analyses, and methodological innovations that address, but are not limited to, the following themes: (1) novel digital phenotyping and AI-driven risk prediction models for incident CVDs and recurrent cerebrovascular events; (2) wearable and implantable sensor technologies for continuous haemodynamic and neurovascular monitoring; (3) personalised decision-support algorithms integrating multi-omics, imaging, and real-world data; (4) digital interventions for behaviour change, self-management, and caregiver support in chronic CVD populations; (5) implementation science and health-economic evaluations of digital precision pathways in routine clinical practice; (6) data privacy, algorithmic fairness, and regulatory frameworks for AI-based cardiovascular diagnostics; and (7) patient-reported outcomes and human-centred design in digital health ecosystems. By bringing together interdisciplinary contributions from clinical medicine, biomedical engineering, data science, and public health, this issue seeks to advance the translation of digital precision health innovations from bench to bedside, ultimately improving outcomes for the millions affected by cardiovascular and cerebrovascular diseases worldwide.

You may choose our Joint Special Issue in Biomedicines.

Prof. Dr. Dafang Chen
Guest Editor

Manuscript Submission Information

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• digital health
• precision medicine
• cardiovascular disease
• cerebrovascular disease
• artificial intelligence
• wearable devices
• remote monitoring
• risk prediction
• digital therapeutics
• implementation science