A new AI model can help radiologists distinguish COVID-19 from non-COVID 19 pneumonia when reading chest CT examinations. The researchers behind this new algorithm shared their findings in Radiology.

“It has been hypothesized that COVID-19 infection is difficult to contain because of its potential transmission from asymptomatic carriers,” wrote lead author Harrison X. Bai, MD, Rhode Island Hospital in Providence, and colleagues. “Common symptoms include fever, cough, and dyspnea while the disease has potential to cause a host of severe and potentially fatal cardiorespiratory complications in vulnerable populations—particularly the elderly with comorbid conditions. While distinguishing COVID-19 from normal lung or other lung pathologies such as cancer on chest CT may be straightforward, a major hurdle in controlling the current pandemic is making out subtle radiological differences between COVID-19 and pneumonia of other etiology.”

Bai et al. gathered imaging data from 521 COVID-19 patients treated in China or the United States from January to April 2020. Findings from 665 pneumonia patients who did not have COVID-19 were also collected; those patients were treated in China or the United States from Jan. 1, 2017, to Dec. 31, 2019.

Source: www.aiin.healthcare