Your Hosts: Fred and Melody
Topic: The University of Leeds developed an AI system called Optimise that analyzed health records of over 2 million people to identify those at high risk for heart problems.
🪢Of the 2 million records scanned, over 400,000 people (20%) were identified as high-risk for conditions like heart failure, stroke and diabetes. This high-risk group accounted for 74% of heart-related deaths.
🪢In a pilot study of 82 high-risk patients identified by Optimise:
- 20% were found to have undiagnosed moderate or high-risk chronic kidney disease
- Over 50% with high blood pressure were given different medication to better manage their heart risk
🪢The AI approach could allow earlier treatment and help relieve pressure on the NHS by preventing conditions from worsening.
🪢This aligns with other AI initiatives in cardiovascular care:
- AI tools have shown promise in detecting heart valve disease and predicting cardiovascular risk from tests like ECGs and retinal imaging.
- AI-enabled digital stethoscopes were found to be more accurate than traditional methods in detecting heart valve disease in primary care settings.
- Deep learning models analyzing retinal images have demonstrated effectiveness in predicting cardiovascular event risk in prediabetic and diabetic patients.
🪢AI is being applied across various aspects of cardiovascular medicine, including risk assessment, diagnosis, treatment optimization, and patient monitoring.
🪢Benefits of AI in cardiovascular care include:
- More accurate and personalized risk prediction
- Earlier detection of heart conditions
- Improved diagnostic accuracy
- Optimization of treatments
- Enhanced patient monitoring and early warning systems
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