Long COVID may be too big a problem for humans to solve—alone, at least.
Increasingly, researchers are turning to artificial intelligence to help them sort through the electronic medical records of millions of long-COVID patients in hopes of better understanding the enigmatic condition with hundreds of potential symptoms.
In some cases, A.I. is helping patients: In a study published last month in The Lancet Digital Health, researchers trained three machine-learning models to identify potential long-COVID patients among hundreds who previously had COVID. Both the models and humans agreed on probable “long haulers” in the vast majority of cases, showing that A.I. can help flag patients who have a high probability of experiencing the chronic condition and get them to care.
Fei Wang, assistant professor of health care policy and research at Weill Cornell Medicine in New York, is coauthor of a recently published study that examined patterns of diagnoses in long-COVID patients.
The researchers used machine learning to examine the electronic health records of thousands of patients and found four patterns among long-COVID patients, he said:
- More severe patients with blood and heart issues, many of whom likely were infected during the initial wave to hit New York City in the spring of 2020. This group had the largest number of patients with preexisting conditions.
- More mild patients with respiratory issues accompanied by sleep problems.
- Patients with new musculoskeletal complaints and neuropsychiatric problems.
- Patients who now suffer from gastrointestinal issues, including abdominal pain.
