Stanford’s Nigam Shah and Joshua Knowles are using machine learning to search for people with familial hypercholesterolemia, a genetic disorder that causes high levels of LDL cholesterol in the blood.
Only a 10 percent of people with the disorder are aware of it, and it is often diagnosed after a cardiac event — the risk of which can be dramatically reduced with early treatment. (Men with the disorder have a 50 percent chance of having a heart attack by age 50; women have a 30 percent chance by age 60.)
Using electronic health records, the researchers identified 120 people known to have FH from Stanford’s network, and others with high LDL who don’t have the genetic disorder.
Algorithms then spotted people with FH by analyzing records and identifying cholesterol levels, age, and prescribed drugs. The algorithms then looked for and identified undiagnosed FH within the health record data.
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