welcomes you to the new, improved website!This study explores the use of artificial intelligence (AI) for auscultation in diagnosing heart failure in Sub-Saharan Africa, highlighting its potential to improve access to cardiovascular care in resource-limited settings. The research demonstrates that AI-based auscultation tools can effectively identify heart failure, offering a solution for early detection and management in regions with limited specialist availability. This approach may help bridge gaps in cardiovascular health equity by supporting timely diagnosis and intervention.
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AI-Enabled Digital Auscultation for Detecting Heart Failure With Reduced Ejection Fraction in Sub-Saharan Africa: The DAMSUN-HF Study
Submitted by: Joel Dunning
Source: Circulation
Keywords:
Author(s): Alexis K. Okoh, Lambert T. Appiah, Yaw A. Wiafe, Michael K. Amponsah, Setri S. Fugar, Ebru Ozturk, Yaw Adu-Boakye, Isaac Kofi Owusu, Bernard Cudjoe Nkum, Bert-Jan van den Born, Charles Agyemang, Amit J. Shah, Modele O. Ogunniyi
