{"id":628690,"date":"2026-09-27T02:14:37","date_gmt":"2026-09-27T02:14:37","guid":{"rendered":"https:\/\/www.newsbeep.com\/il\/628690\/"},"modified":"2026-09-27T02:14:37","modified_gmt":"2026-09-27T02:14:37","slug":"ascvd-risk-assessment-enhanced-by-ai-platform-emj","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/il\/628690\/","title":{"rendered":"ASCVD Risk Assessment Enhanced by AI Platform \u2013 EMJ"},"content":{"rendered":"

AI-powered cardiovascular care system demonstrated potential to improve cardiovascular health literacy and early risk detection, according to a new study.\u00a0<\/p>\n

Integrated Approach to Cardiovascular Risk Education\u00a0<\/p>\n

Cardiovascular diseases<\/a> remain a major global health challenge, with barriers such as low health literacy, misinformation, language differences, and fragmented patient engagement continuing to affect prevention and long-term management.\u00a0<\/p>\n

To address these issues, researchers developed a comprehensive digital platform that integrates a Digital Human Agent, artificial intelligence (AI), natural language processing, and guideline-based ASCVD<\/a> risk assessment within a single system.\u00a0<\/p>\n

Accessible via both mobile and web platforms, the system uses bilingual English and Arabic voice or text interactions to provide personalised cardiovascular education and risk-based recommendations.\u00a0\u00a0<\/p>\n

The AI assistant was designed to simplify medical terminology and deliver tailored information according to an individual\u2019s cardiovascular risk level.\u00a0\u00a0<\/p>\n

A corresponding clinician dashboard allows cardiologists to monitor patient data, review risk trends, and communicate directly with users in real time.\u00a0<\/p>\n

ASCVD Risk Assessment Integrated with AI Communication\u00a0<\/p>\n

The platform incorporates a validated ASCVD risk assessment model aligned with established cardiovascular prevention guidelines.\u00a0\u00a0<\/p>\n

Users provide information including age, cholesterol levels, blood pressure, smoking status, and diabetes status.\u00a0\u00a0<\/p>\n

The system then generates a 10-year ASCVD risk estimate and categorises individuals into low, borderline, intermediate, or high-risk groups.\u00a0<\/p>\n

Researchers verified the accuracy of the ASCVD calculations against established reference cases, with all tested scenarios matching published risk estimates.\u00a0<\/p>\n

Once risk scores are generated, the AI converts complex clinical information into accessible explanations and personalised recommendations intended to support patient understanding and engagement.\u00a0<\/p>\n

The Digital Human Agent delivers these recommendations through conversational interactions using both spoken and written responses.\u00a0\u00a0<\/p>\n

Risk guidance is adapted according to the user\u2019s preferred language and calculated cardiovascular risk category.\u00a0<\/p>\n

Early Evaluation Shows Promise\u00a0<\/p>\n

Initial evaluation focused on software validation, expert review, and functional testing using synthetic patient data rather than clinical outcomes.\u00a0\u00a0<\/p>\n

Feedback from healthcare professionals highlighted demand for simplified medical language, interactive educational tools, and personalised risk information.\u00a0\u00a0<\/p>\n

Surveys also demonstrated strong public interest in mobile health applications and tailored cardiovascular guidance.\u00a0<\/p>\n

According to the researchers, the system may help strengthen digital health literacy, improve patient engagement, and support closer collaboration between patients and cardiologists.\u00a0\u00a0<\/p>\n

However, they acknowledged that formal clinical validation, assessment of health outcomes, and real-world testing remain necessary before broader implementation.\u00a0\u00a0<\/p>\n

Future work will focus on longitudinal risk tracking, predictive disease modelling, and controlled evaluations of user engagement and comprehension.\u00a0<\/p>\n

Reference\u00a0<\/p>\n

Al-Rajab M et al. My Heart: a personalized interactive cardiovascular care system using artificial intelligence. Sci Rep. 2026;DOI:10.1038\/s41598-026-68939-z.\u00a0<\/p>\n

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