Application of artificial intelligence in diagnosing COVID-19 disease symptoms on chest X-rays: A systematic review.

This systematic review focuses on using artificial intelligence (AI) to detect COVID-19 infection with the help of X-ray images. Methodology: In January 2022, the authors searched PubMed, Embase and Scopus using specific medical subject headings terms and filters. All articles were independently reviewed by two reviewers. All conflicts resulting from a misunderstanding were resolved by a third independent researcher. After assessing abstracts and article usefulness, eliminating repetitions and applying inclusion and exclusion criteria, six studies were found to be qualified for this study. Results: The findings from individual studies differed due to the various approaches of the authors. Sensitivity was 72.59%-100%, specificity was 79%-99.9%, precision was 74.74%-98.7%, accuracy was 76.18%-99.81%, and the area under the curve was 95.24%-97.7%. Conclusion: AI computational models used to assess chest X-rays in the process of diagnosing COVID-19 should achieve sufficiently high sensitivity and specificity. Their results and performance should be repeatable to make them dependable for clinicians. Moreover, these additional diagnostic tools should be more affordable and faster than the currently available procedures. The performance and calculations of AI-based systems should take clinical data into account.

Cardiovascular System during SARS-CoV-2 Infection.

SARS-CoV-2 virus can not only damage the respiratory system but may also pose a threat to other organs, such as the heart or vessels. This review focuses on cardiovascular complications of COVID-19, including acute cardiac injury, arrhythmias, biomarkers, accompanying comorbidities and outcomes in patients diagnosed with SARS-CoV-2 infection. The research was conducted on the databases: PubMed, Springer, ScienceDirect, UpToDate, Oxford Academic, Wiley Online Library, ClinicalKey. Fifty-six publications from 1 November 2020 till 15 August 2021 were included in this study. The results show that cardiac injury is present in about 1 in 4 patients with COVID-19 disease, and it is an independent risk factor, which multiplies the death rate several times in comparison to infected patients without myocardial injury. New-onset cardiac injury occurs in nearly every 10th patient of the COVID-19-suffering population. Comorbidities (such as hypertension, cardiovascular disease and diabetes) severely deteriorate the outcome. Therefore, patients with SARS-CoV-2 infection should be carefully assessed in terms of cardiac medical history and possible cardiological complications.