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AI To Predict Which COVID-19 Patients Will Develop Respiratory Disease Developed: Study

Scientists have developed an AI tool that may accurately predict which patients newly infected with COVID-19 would go on to develop severe respiratory disease


Scientists in the US and China have developed an artificial intelligence (AI) tool that may accurately predict which patients newly infected with the COVID-19 virus would go on to develop severe respiratory disease. The study, published in the journal Computers, Materials & Continua, also revealed the best indicators of future severity and found that they were not as expected.

"While work remains to further validate our model, it holds promise as another tool to predict the patients most vulnerable to the virus, but only in support of physicians' hard-won clinical experience in treating viral infections," said Megan Coffee, a clinical assistant professor at New York University (NYU) in the US.

The goal of the research

"Our goal was to design and deploy a decision-support tool using AI capabilities -- mostly predictive analytics -- to flag future clinical coronavirus severity," said Anasse Bari, a clinical assistant professor at New York University. "We hope that the tool, when fully developed, will be useful to physicians as they assess which moderately ill patients really need beds, and who can safely go home, with hospital resources stretched thin," Bari said.

For the study, demographic, laboratory, and radiological findings were collected from 53 patients as each tested positive in January for the SARS-CoV2 virus at the two Chinese hospitals. Symptoms were typically mild, to begin with, including cough, fever, and stomach upset. In a minority of patients, however, severe symptoms developed with a week, including pneumonia.

The goal of the study was to determine whether AI techniques could help to accurately predict which patients with the virus would go on to develop Acute Respiratory Distress Syndrome (ARDS), the fluid build-up in the lungs that can be fatal in the elderly. The researchers designed computer models that make decisions based on the data fed into them, with programmes getting "smarter" the more data they consider.

They tracked a series of decisions between options, and that model the potential consequences of choices at each step in a pathway. The researchers were surprised to find that characteristics considered to be hallmarks of COVID-19, like certain patterns seen in lung images, fever, and strong immune responses, were not useful in predicting which of the many patients with initial, mild symptoms would go to develop severe lung disease.

Risk of ARDS was predicted with up to 80% accuracy

Neither were age and gender helpful in predicting serious disease, although past studies had found men over 60 to be at higher risk. The new AI tool found that changes in three features -- levels of the liver enzyme alanine aminotransferase (ALT), reported myalgia, and haemoglobin levels -- were most accurately predictive of subsequent, severe disease. The team reported being able to predict the risk of ARDS with up to 80% accuracy.

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ALT levels -- which rise dramatically as diseases like hepatitis damage the liver -- were only a bit higher in patients with COVID-19, researchers said, but still featured prominently in the prediction of severity. Deep muscle aches (myalgia) were also more commonplace, and have been linked by past research to higher general inflammation in the body, they said.

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Higher levels of haemoglobin, the iron-containing protein that enables blood cells to carry oxygen to bodily tissues, were also linked to later respiratory distress, according to the researchers. The team is now looking to further refine the tool with data from New York and hope it is ready to deploy sometime in April. The research comes at a time when the death toll because of the Coronavirus pandemic has surpassed 40,000.

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(With PTI inputs)

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