AI accelerates breakthroughs in long Covid, fatigue disorders

Artificial Intelligence (AI) has joined the efforts in combating the notoriously hard-to-diagnose diseases of extreme tiredness such as myalgic encephalomyelitis (ME) and long Covid.

In a new study, based on abnormal physical factors relating to ME, the researchers found 90 percent accuracy in identifying the cases of ME by using a new AI platform to spot markers for the condition from routine lab tests including for blood and stools.

These unprecedented findings offer a promising opportunity to identify and accurately diagnose a class of medical complexities that have for many years impaired patients and perplexed doctors.

According to Julia Oh, a Duke University microbiologist, who led the study in collaboration with researchers at The Jackson Laboratory biomedical research institute, “Our goal is to build a detailed map of how the immune system interacts with gut bacteria and the chemicals they produce.

“By connecting these dots we can start to understand what’s driving the disease and pave the way for genuinely precise medicine that has long been out of reach,” she added.

"The increasing use of AI in decoding chronic fatigue syndrome has proved a promising avenue of research in this domain," explained Janet Scott, clinical lecturer in infectious disease at the MRC-University of Glasgow Centre for Virus Research.

“Instead of hunting for single causes, this approach could help us think about these complex conditions as network diseases. The problem may not be one broken component but disrupted communication between systems,” Scott said.

The ME conditions affect tens of millions of people globally. According to the World Health Organization (WHO), around 6 percent of those who contract Covid-19 then suffer long Covid and chronic fatigue syndrome.