Artificial Intelligence in Women’s Cardiovascular Health: Advances in Diagnosis, Screening, and Risk Prediction

Dear Colleagues,

Cardiovascular disease (CVD) remains the leading cause of mortality among women worldwide, yet it is frequently underdiagnosed, underestimated, and mischaracterized due to sex-specific pathophysiology and atypical clinical presentation. Women often present with non-classical symptoms, microvascular dysfunction, and diffuse atherosclerotic patterns that differ significantly from traditional male-centric diagnostic models.

In addition, several women-specific biological and life-stage factors substantially modify cardiovascular risk, including:

(i) Pregnancy-related complications (e.g., preeclampsia, gestational hypertension, gestational diabetes) that serve as early markers of future cardiovascular disease and present opportunities for early screening and monitoring.

(ii) Peripartum cardiomyopathy and adverse ventricular remodeling, which necessitate advanced diagnostic imaging and surveillance protocols.

(iii) Hormonal transitions such as menopause and estrogen decline affecting vascular stiffness and metabolic regulation, highlighting the need for novel biomarkers and diagnostic tools.

(iv) Polycystic Ovary Syndrome (PCOS) associated with insulin resistance and endothelial dysfunction.

(v) Autoimmune and inflammatory disorders disproportionately affecting women, often complicating early diagnosis and risk assessment.

(vi) Psychosocial stress, depression, and gender-specific socioeconomic determinants of health.

These factors contribute not only to short-term maternal risk but also to accelerated long-term cardiovascular morbidity and mortality across the lifespan. Despite this, diagnostic and risk prediction models, as well as clinical guidelines, remain insufficiently tailored to women-specific physiology. Artificial Intelligence (AI), including machine learning, deep learning, multimodal data fusion, and generative AI frameworks, offers transformative potential for early and accurate diagnosis, risk prediction, imaging-based phenotyping, transcriptomic and biomarker integration, non-invasive screening, and personalized diagnostic decision support systems. A dedicated Special Issue would provide a focused and interdisciplinary platform to advance sex-specific cardiovascular modeling, explainable AI systems, and precision diagnostic and risk stratification strategies specifically designed for women’s cardiovascular health.

Dr. Jasjit S. Suri
Prof. Dr. Luca Saba
Guest Editors

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