CFC Ogbuefi
Cardiovascular disease (CVD) remains the leading cause of mortality in the United States, with persistent disparities driven by limitations in traditional risk stratification models and fragmented healthcare data systems. This conceptual technical report presents the Artificial Intelligence-Driven Integrated Risk Assessment of Cardiovascular Disease (AIRA-CVD) framework, a multimodal predictive architecture designed to integrate clinical diagnostic informatics, inflammatory biomarker signatures, and histopathological validation of vascular remodeling. The proposed framework leverages structured and unstructured electronic health record (EHR) data, cardiovascular imaging, and circulating biomarkers, including high-sensitivity C-reactive protein (hs-CRP) and interleukin-6 (IL-6), to generate individualized risk predictions. A distinguishing feature of AIRA-CVD is the incorporation of histopathological vascular remodeling as a ground-truth calibration standard, which is designed to enhance interpretability and is hypothesized to mitigate bias associated with traditional proxy-based models. The framework further integrates human-in-the-loop clinical oversight and continuous performance auditing to align with emerging ethical governance standards. By linking computational modeling with biological validation, AIRA-CVD is designed to provide a scalable and equity-centered approach to precision cardiovascular risk assessment and, if prospectively validated, may have the potential to contribute to improved clinical outcomes and reduced health disparities.