This story was originally published in our July/August 2022 issue as "Ghosts in the Machine." Click here to subscribe to read more stories like this one.
If a heart attack isn’t documented, did it really happen? For an artificial intelligence program, the answer may very well be “no.” Every year, an estimated 170,000 people in the United States experience asymptomatic — or “silent” — heart attacks. During these events, patients likely have no idea that a blockage is keeping blood from flowing or that vital tissue is dying. They won’t experience any chest pain, dizziness or trouble breathing. They don’t turn beet red or collapse. Instead, they may just feel a bit tired, or have no symptoms at all. But while the patient might not realize what happened, the underlying damage can be severe and long-lasting: People who suffer silent heart attacks are at higher risk for coronary heart disease and stroke and are more likely to die within the following 10 years.
But if a doctor doesn’t diagnose that attack, it won’t be included in a patient’s electronic health records. That omission can come with dangerous consequences. AI systems are trained on health records, sifting through troves of data to study how doctors treated past patients and make predictions that can inform decisions about future care. “That’s what makes a lot of medical AI very challenging,” says Ziad Obermeyer, an associate professor at the University of California, Berkeley, who studies machine learning, medicine and health policy. “We almost never observe the thing that we really care about.”
