Thanks to big data, doctors and scientists are making progress on being able to predict heart disease and find which treatments are the most effective.

Our Current Fight Against Heart Disease

As it stands right now, diagnosing heart disease requires a person to take a variety of medical tests to find. There is often minimal symptoms that can clue in a person that they have heart disease, except massive things like a heart attack.

Because there are minimal noticeable symptoms for heart disease, doctors have to look for clues in every checkup, like high blood pressure, being overweight, or having difficulty breathing.

When it comes to treating heart disease, we have methods for decreasing the chances of a dangerous incident, like a heart attack or stroke, but no clear way to cure it. Treatment methods can include medication to lower blood pressure or thin the blood to decrease the chance of clotting and stroke, getting a pacemaker, and more.

Since we have no clear way to cure heart disease, it comes down to predicting and preventing it from becoming a problem in people’s lives. This is where big data can do a lot of good.

Finding the Patterns of Heart Disease

Big data can be extremely useful in finding the patterns that lead to patients getting heart disease. By taking the medical and personal information of people with heart disease, scientists can find patterns that could associate with heart disease. By combining these patterns, doctors are finding what people are more at risk for heart disease and trying to predict things like when people will have heart attacks.

 

This article originally appeared in datafloq.com.  To read the full article, click here