About the solution
When Sofia was 10, she witnessed her grandmother collapsing because of a heart attack. “That was something that struck me as terrifying — how someone can seem fine one moment and then collapse the next,” said Sofia. From her experience, she had the idea to create a device able to predict heart disease risk.
Sofia reviewed existing scientific literature and spoke with several cardiac experts and cardiologists while at high school. After taking a class on machine learning, Sofia saw how to apply the technology to predict heart disease risk.
In 2019, Sofia founded the startup Qardian Labs to bring her heart disease prediction solution to market. The HIPAA-compliant software fuels its algorithm with 11 patient data metrics to determine heart disease risk in a few seconds. The metrics include blood sugar, cholesterol, age, sex, maximum heart rate achieved, and other physical test results.
“The algorithm uses a deep neural framework to learn relationships between the 11 patient data points,” said Sofia. “That’s particularly significant since most doctor screening tools only analyze numbers one-by-one.”
The dashboard shows the patient’s heart disease probability risk, which the doctor can use to develop a treatment plan.
The startup has undergone a pilot in 2019, in the University of Tennessee Medical Center’s sports medicine practice to use echocardiogram data as a standard screening procedure for student-athletes.
This solution shall not include mention to the use of drugs, chemicals or biologicals (including food); invasive devices; offensive, commercial or inherently dangerous content. This solution was not medically validated. Proceed with caution! If you have any doubts, please consult with a health professional.
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