Targeted Cardiovascular Screening
New Machine-Learning Model Deployed Across Five U.S. Health Systems to Prioritize Cardiovascular Screening
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Key Points
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The Family Heart Foundation’s FIND Lp(a) machine-learning model has already been deployed at five large U.S. health-care systems through the FIND Lp(a) Program.
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The study found that patients identified by the model were more than 2.2 times as likely to have high Lp(a), defined as at least 125 nmol/L, as the overall ASCVD population in the Family Heart Database; further retrospective and prospective validation is still underway.
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Family Heart Foundation vice president Diane MacDougall said that although recent U.S. dyslipidemia guidelines recommend Lp(a) screening for all adults, integrating universal screening into routine care could take “many years, if not decades,” making targeted screening a transitional strategy.
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The semiconductor rebound cited in the business report included Nvidia second-quarter sales growth of 106% to $96.2 billion and a 221% increase in Broadcom’s AI sales; expectations surrounding OpenAI’s GPT-6 Astra were also described as a potential driver of further computing demand.
The Family Heart Foundation has deployed its artificial intelligence model to identify patients at high risk for dangerous cholesterol levels at five major U.S. health systems. Mirage News reports that the FIND Lp(a) machine-learning model can spot people more than twice as likely to have elevated lipoprotein(a) — a type of cholesterol linked to heart disease — potentially helping doctors prioritize screening before broader adoption of universal testing.
The breakthrough addresses a screening gap. Mirage News notes that while recent U.S. guidelines recommend checking all adults for high Lp(a), rolling out universal screening nationwide could take "many years, if not decades." The AI model offers a faster middle path: using data to find the highest-risk patients now while the medical system prepares for wider testing.
How the AI Model Spots High-Risk Patients
The FIND Lp(a) model uses machine learning to flag cardiovascular disease patients who likely have dangerously high lipoprotein(a) levels. Mirage News states that patients the model identified were 2.2 times more likely to have elevated Lp(a) — defined as at least 125 nmol/L — compared to the overall heart disease population in the Family Heart Database. The model works by analyzing existing patient data without requiring new tests.
Five Health Systems Now Using the AI Tool
The Family Heart Foundation has begun rolling out its FIND Lp(a) model across five large U.S. hospital networks through the FIND Lp(a) Program. Mirage News reports the deployment is part of a staged approach to validate the model's real-world performance. Doctors at these systems can now use the AI to identify patients who need urgent Lp(a) screening before heart problems develop.
A Bridge Strategy Until Universal Screening Arrives
Diane MacDougall, the Family Heart Foundation's vice president, explained the practical challenge. Mirage News quotes her saying that integrating universal Lp(a) screening for all U.S. adults into routine medical care could take "many years, if not decades." The AI model offers a targeted alternative: identify and treat the highest-risk patients immediately while the healthcare system gradually shifts toward checking everyone.
Ongoing Validation Before Wider Rollout
The study published in JACC: Advances is still early-stage. Mirage News notes that both retrospective — looking back at past data — and prospective validation — testing on new patients going forward — are still underway. This careful verification process helps ensure the model works reliably across different hospitals and patient populations before it expands to hundreds of healthcare centers nationwide.
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