ABSTRACT:
Cardiovascular disease (CVD) poses a significant burden in low-resource settings, where scalable, context-specific interventions remain scarce. Addressing this gap requires rapid, evidence-driven innovation tailored to local needs. This study presents an AI-augmented workflow leveraging Google’s NotebookLM and Gemini tools to accelerate the development of a cardiovascular minimum viable product (MVP) for such settings. The approach adapts a proven workflow by uploading global health documents, including WHO reports, clinical guidelines, and community assessments, into NotebookLM for comprehensive analysis. Targeted queries extract key insights on regional CVD risk factors, diagnostic tools, and adherence barriers. These insights are synthesised in Gemini to ideate and validate an MVP featuring community health worker-led screening, low-literacy education, and offline functionality. The entire process, from evidence curation to MVP prototype, was completed within one day, demonstrating substantial time savings compared to traditional methods. This workflow highlights AI’s potential as a force multiplier for health equity by enabling rapid, context-aware solution design grounded in authoritative sources. The resulting MVP offers a practical, cost-effective tool to improve cardiovascular care in underserved communities, with implications for broader application in global health innovation.