Keeping aside the differences, the whole world is fighting a common enemy, COVID-19. The virus that causes it is called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). So far, there has been no drug or vaccine to treat this global pandemic, which has taken around 82,000 lives. The havoc that the disease has wreaked worldwide is an unprecedented one and nations were not prepared for this. Researchers are racing against time to find a cure for this disease. Any breakthrough in research seems like a light at the end of the tunnel.
Researchers from the University of Copenhagen have come up with a unique solution for making use of artificial intelligence (AI) in the current outbreak. Use of AI could help assess the risk of a patient with coronavirus requiring ventilators. Ventilators have garnered immense importance in the treatment of this outbreak worldwide. However, there is not enough supply of ventilators across the globe. Given the huge number of patients being admitted at every hour, many hospitals are already facing a shortage of ventilators or will soon be running out of them. As such, it is important to assess which of the patients would need ventilators and who would not. Such an assessment could help in the distribution of resources properly and save time.
Analysis of Common Traits of Patients who Needed Ventilation to Help Assess the Risk
A team of researchers from the University of Copenhagen has come up with an artificial intelligence-powered system that will assess the patients’ risk for intensive care or ventilator. The algorithms will make an analysis of the colossal amount of data extracted from various sources. It will explore the common traits between SARS-CoV-2 infected patients who were moved to ICU or needed ventilators ultimately.
This artificial intelligence-powered system will look at the common traits between the condition of patients who eventually needed ventilators or intensive care. This system will delve deeper into the aspects of the patients’ condition such as the application of certain pharmaceuticals, white blood cells and others. What comes up as a common trait for patients who ultimately needed ventilation is likely to emerge as the deciding factor. The information, thus gathered, will then be utilized to compare it with the condition of newly hospitalized patients. It will enable doctors to predict the need for ventilation of a patient