Deep Learning for Heart Failure Diagnostics and Therapeutic Discovery
Advancing Heart Failure Care With AI-Enhanced Diagnostics

The objectives
Enhancing Diagnostic Efficiency with AI
Facilitating Drug Discovery and Longitudinal Monitoring
Scaling Data for Machine Learning Applications

The impact
The ATTRaCT network’s adoption of AI-based tools, such as US2.AI, has drastically accelerated heart failure diagnostics by reducing analysis time from 30 minutes to just 2 minutes. This improvement allows clinicians to make faster, more accurate decisions with minimal variability, ultimately enhancing patient care. In addition to streamlining diagnostics, the project has advanced cardiovascular drug discovery and patient monitoring. By leveraging deep learning, the initiative supports comprehensive data analysis that identifies therapeutic targets and enables long-term health tracking, paving the way for personalised treatment options.
The network’s global reach is also notable, spanning 50 sites across 12 countries and establishing a scalable platform for DICOM data collection. This vast data infrastructure supports large-scale machine learning applications, positioning A*STAR to make significant contributions to cardiovascular care on an international scale. Furthermore, US2.AI's mobile, non-invasive echocardiography decision support tool offers a cost-effective solution, expanding access to high-quality diagnostics, especially in areas with limited traditional resources. This approach broadens the accessibility of quality healthcare, making advanced cardiovascular care more inclusive and affordable.
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