A new artificial intelligence (AI) tool can make a 90 percent prediction whether a person infected with COVID-19 will die or survive, research at the University of Copenhagen showed.
Researchers obtained data from almost 4,000 COVID-19 patients to instruct their AI tools and then find patterns in that data. The study published in the journal Scientific Reports suggested that body mass index (BMI), gender, and high blood pressure are among the most heavily weighted factors. This can be used to build a model that can predict the chances of dying from the virus. Other factors associated with higher mortality are neurological diseases, COPD, asthma, diabetes, and heart disease.
The results of the research were based on patient data from the Capital Region of Denmark and Region Zealand which demonstrated that artificial intelligence (AI) tool can, with up to 90 percent accuracy, determine whether a person who is not yet infected will die of Covid-19 or not if contracted the virus. The tool will also help policymakers in determining the priority groups for vaccination.
Since the first wave of the coronavirus pandemic, researchers have been working to develop models that can predict how severely people will be affected by Covid-19, based on disease history and other health data.
Professor Mads Nielsen of the University of Copenhagen’s Department of Computer Science said: “We began working on the models to assist hospitals, as, during the first wave, they feared that they did not have enough respirators for intensive care patients. Our new findings could also be used to carefully identify who needs a vaccine.”
The researchers designed a computer program with health data from 3,944 Danish covid-19 patients for the study.
“Our results demonstrate, unsurprisingly, that age and BMI are the most decisive parameters for how severely a person will be affected by Covid-19. But the likelihood of dying or ending up on a respirator is also heightened if you are male, have high blood pressure or neurological disease,” explained Mads Nielsen.
The researchers are working with the Capital Region of Denmark and hope that the model could soon be used to help hospitals predict 80% whether a person will need a respirator if admitted to the hospital with Covid-19.
Read the study paper in the journal Nature.