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Incorporating AI into cardiovascular diseases prevention–insights from Singapore

Authors :
Mayank Dalakoti
Scott Wong
Wayne Lee
James Lee
Hayang Yang
Shaun Loong
Poay Huan Loh
Sara Tyebally
Andie Djohan
Jeanne Ong
James Yip
Kee Yuan Ngiam
Roger Foo
Source :
The Lancet Regional Health. Western Pacific, Vol 48, Iss , Pp 101102- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Summary: Improved upstream primary prevention of cardiovascular disease (CVD) would enable more individuals to lead lives free of CVD. However, there remain limitations in the current provision of CVD primary prevention, where artificial intelligence (AI) may help to fill the gaps. Using the data informatics capabilities at the National University Health System (NUHS), Singapore, empowered by the Endeavour AI system, and combined large language model (LLM) tools, our team has created a real-time dashboard able to capture and showcase information on cardiovascular risk factors at both individual and geographical level- CardioSight. Further insights such as medication records and data on area-level socioeconomic determinants allow a whole-of-systems approach to promote healthcare delivery, while also allowing for outcomes to be tracked effectively. These are paired with interventions, such as the CHronic diseAse Management Program (CHAMP), to coordinate preventive cardiology care at a pilot stage within our university health system. AI tools in synergy allow the identification of at-risk patients and actionable steps to mitigate their health risks, thereby closing the gap between risk identification and effective patient care management in a novel CVD prevention workflow.

Details

Language :
English
ISSN :
26666065
Volume :
48
Issue :
101102-
Database :
Directory of Open Access Journals
Journal :
The Lancet Regional Health. Western Pacific
Publication Type :
Academic Journal
Accession number :
edsdoj.689979fb1d4198ba289e076c29a62f
Document Type :
article
Full Text :
https://doi.org/10.1016/j.lanwpc.2024.101102