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AI model can read ECGs to identify female patients at higher risk of heart disease
A new AI model can flag female patients who are at higher risk of heart disease based on an electrocardiogram (ECG). The researchers say the algorithm, designed specifically for female patients, could enable doctors to identify high-risk women earlier, enabling better treatment and care. Details
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AI model can read ECGs to identify female patients at higher risk of heart disease
A new AI model can flag female patients who are at higher risk of heart disease based on an electrocardiogram (ECG). The researchers say the algorithm, designed specifically for female patients, could enable doctors to identify high-risk women earlier, enabling better treatment and care. Details
[3]
New AI tool detects elevated heart disease risk in women using ECG
Imperial College LondonFeb 25 2025 A new AI model can flag female patients who are at higher risk of heart disease based on an electrocardiogram (ECG). The researchers say the algorithm, designed specifically for female patients, could enable doctors to identify high-risk women earlier, enabling
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A new AI model developed by researchers at Imperial College London can identify female patients at higher risk of heart disease by analyzing electrocardiograms (ECGs), potentially improving early detection and treatment for women.

Researchers at Imperial College London have developed a groundbreaking AI model that can identify female patients at higher risk of heart disease by analyzing electrocardiograms (ECGs). This innovative approach, detailed in a study published in The Lancet Digital Health, could significantly improve early detection and treatment of cardiovascular disease in women
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.The research team, led by Dr. Arunashis Sau and Dr. Fu Siong Ng, used artificial intelligence to analyze over one million ECGs from 180,000 patients, including 98,000 women. The AI model developed a score that measures how closely an individual's ECG matches 'typical' patterns for men and women
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.Key findings include:
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.The study highlights a critical issue in cardiovascular health: the misconception that women are at lower risk of heart disease. Dr. Sau emphasized, "Our work has underlined that cardiovascular disease in females is far more complex than previously thought"
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.Some alarming statistics include:
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Dr. Fu Siong Ng noted, "Many of the women identified were in fact at even higher risk than the 'average' man. If it becomes used widely, over time the AI model may reduce gender differences in cardiac care, and improve outcomes for women at risk of heart disease"
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.The research group has also developed a related AI-ECG risk estimation model called AIRE, which can predict patients' risk of developing and worsening disease from an ECG. NHS trials for AIRE are planned for late 2025
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.Dr. Sonya Babu-Narayan, Clinical Director at the British Heart Foundation, commented on the potential of this research: "Harnessing the potential of this type of research could help better identify those patients at highest risk of future heart problems and reduce the gender gap in heart care outcomes"
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.However, she cautioned that one test alone would not solve all issues, stating, "Ensuring every person gets the right heart care they need when they need it will require change in every part of our healthcare system"
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.This research, funded by the British Heart Foundation and supported by the NIHR Imperial Biomedical Research Centre, represents a significant step forward in addressing gender disparities in cardiac care and improving outcomes for women at risk of heart disease.
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