Heart disease is the leading cause of death in America. One out of every four people who die, pass away because of heart disease.
Thanks to big data though, 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
Early detection is incredibly important to preventing heart disease. If doctors can identify people at risk for heart disease earlier in their lives than they can coach patients on what they need to do to prevent it. That way, those people can create habits earlier in their lives to stay healthy and lower the risk for 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.
Applying these Patterns to Patients
Every person is different. They have unique medical histories, lifestyles, family backgrounds of heart disease, and more, meaning that there is no single treatment that works for everybody.
But, because of the nature of big data and finding patterns, each person can fall into a specific pattern found in the data. The first grouping is people that are at risk for heart disease, and those that aren’t, based on their background and current health. Then, you can break down that first grouping into sub-groups based on their backgrounds, lifestyles, and such.
Along with the data about backgrounds and current health, information is gathered about what treatments they receive and what worked and didn’t. So, when it comes to figuring out the best treatment, there is less experimentation on patients because the data can point doctors on what worked for other patients in similar groups.
Combining AI with Big Data
Finding the patterns and groups in big data is not easy. Luckily, medical science has turned to a very useful tool, artificial intelligence. An AI program from CloudMedx clinical is a leading example of using AI to aggregate, analyze and group big data into information doctors can use. Then, by combining that information with treatment options and results, that AI can then figure out what treatments were the most effective for each group and forward that information to the medical community.
It’s even possible in the future that doctors could send their patient’s information into a collective AI program to determine if patients are at risk for heart disease. Along with collecting more data, the AI also can find patterns that human being might miss and better diagnose people early with potential heart disease.
The Power of Big Data for Healthcare
Big data definitely has a future in the medical world and could be the solution we need to solve many problems. By embracing big data, we could do things like predict future epidemics, eliminate ineffective treatment for diseases, and improve the world’s health as a whole.
While we may never find a cure for heart disease, we can get better at predicting who might have it and what can be done to prevent or minimize it.
