Artificial intelligence (AI) has joined efforts to combat the infamous diagnostic disorders of extreme fatigue, such as muscular encephalomyelitis (ME) and long covid.
In a new study based on abnormal physical factors related to me, the researchers found 90% accuracy in identifying my case using a new AI platform to find markers of condition from routine lab tests such as blood and stool.
These unprecedented findings provide a promising opportunity to identify and accurately diagnose classes of medical complexity that have been bothering patients and confused physicians over the years.
“They're also known as the researchers at the Jackson Institute's Biomedical Institute,” said Julia Oh, a microbiologist at Duke University who led the research in collaboration with researchers at the Jackson Institute's Biomedical Institute.
“By connecting these dots, we understood what drives the illness and remained out of reach for a long time.
“The increased use of AI in decoding chronic fatigue syndrome has proven to be a promising tool for research in this area,” explained Janet Scott, clinical lecturer in infectious diseases at MRC University at the Glasgow Virus Research Center.
“Instead of hunting for a single cause, this approach helps to think of these complex conditions as network diseases. The problem may not be broken ingredients, but rather disrupt communication between systems,” Scott said.
The status of ME affects tens of millions of people around the world. According to the World Health Organization (WHO), about 6% of people contracting for Covid-19 suffer from long Covid and chronic fatigue syndrome.
