The role of artificial intelligence in plain chest radiographs interpretation during the Covid-19 pandemic

Abstract

Artificial intelligence (AI) plays a crucial role in the future development of all healthcare sectors ranging from clinical assistance of physicians by providing accurate diagnosis, prognosis and treatment to the development of vaccinations and aiding in the combat against the Covid-19 global pandemic. AI has an important role in diagnostic radiology where the algorithms can be trained by large datasets to accurately provide a timely diagnosis of the radiological images given. This has led to the development of several AI algorithms that can be used in regions of scarcity of radiologists during the current pandemic by simply denoting the presence or absence of Covid-19 pneumonia in PCR positive patients on plain chest radiographs as well as in helping to levitate the over burdened radiology departments by accelerating the time for report delivery. Plain chest radiography is the most common radiological study in the emergency department setting and is readily available, fast and a cheap method that can be used in triaging patients as well as being portable in the medical wards and can be used as the initial radiological examination in Covid-19 positive patients to detect pneumonic changes. Numerous studies have been done comparing several AI algorithms to that of experienced thoracic radiologists in plain chest radiograph reports measuring accuracy of each in Covid-19 patients. The majority of studies have reported performance equal or higher to that of the well-experienced thoracic radiologist in predicting the presence or absence of Covid-19 pneumonic changes in the provided chest radiographs.

Clinical Implication and Prognostic Value of Artificial-Intelligence-Based Results of Chest Radiographs for Assessing Clinical Outcomes of COVID-19 Patients

“…Artificial intelligence (AI) is being widely applied in medicine, and efforts have focused on integrating AI for the efficient diagnosis, treatment, and prediction of outcomes of COVID-19 patients [ 3 , 4 , 5 ]. COVID-19 manifests radiologic abnormalities on chest radiographs (CXR), such as peripherally located increased opacity areas with lower lobe predominance, even though these findings overlap with those of other diseases, such as organizing pneumonia or other infectious diseases [ 6 , 7 ]. These CXR abnormalities were used to develop an AI algorithm to detect COVID-19 infection, and recently some researchers attempted to demonstrate the prognostic implications of detecting CXR abnormalities using AI [ 3 , 8 , 9 , 10 ].…”