AI could help identify coronavirus patients at greatest risk of becoming seriously ill

• Researchers at New York University say their model shows that factors such as age and gender are not the most important indicators of danger
• Increased levels of a liver enzyme, muscle pain and haemoglobin counts were identified as the most important warning signs

Researchers hope that artificial intelligence can help identify which Covid-19 patients will become seriously ill.
An AI algorithm built by New York University researchers found that age, gender, lung image patterns and temperature are not the most useful risk indicators.
Instead, it identified a series of other indicators to predict which newly infected patients would go on to develop severe respiratory disease, according to the study published online March 30 in the journal Computers, Materials & Continua.
In partnership with Chinese doctors, the AI models used data from two hospitals in Wenzhou city, which showed that the three main risk factors were increases in the liver enzyme alanine aminotransferase; myalgias, a type of muscle pain; and rising haemoglobin levels.
The models they built were proven to have 70 to 80 per cent accuracy in predicting severe cases.
The current pandemic is overwhelming health systems around the world and triage tools that help identify those most at risk of severe illnesses may help to allocate resources.
Some patients develop the life-threatening acute respiratory distress syndrome (ARDS) within a matter of hours or days while others show only mild symptoms until they recover.
Although statistics had shown men older than 60 with pre-existing medical conditions tend to be at higher risk, acute respiratory distress and deaths have been seen in all age and gender groups, including people who appear to be young and healthy.