An XAI approach for COVID-19 detection using transfer learning with X-ray images.

The coronavirus disease (COVID-19) has continued to cause severe challenges during this unprecedented time, affecting every part of daily life in terms of health, economics, and social development. There is an increasing demand for chest X-ray (CXR) scans, as pneumonia is the primary and vital complication of COVID-19. CXR is widely used as a screening tool for lung-related diseases due to its simple and relatively inexpensive application. However, these scans require expert radiologists to interpret the results for clinical decisions, i.e., diagnosis, treatment, and prognosis. The digitalization of various sectors, including healthcare, has accelerated during the pandemic, with the use and importance of Artificial Intelligence (AI) dramatically increasing. This paper proposes a model using an Explainable Artificial Intelligence (XAI) technique to detect and interpret COVID-19 positive CXR images. We further analyze the impact of COVID-19 positive CXR images using heatmaps. The proposed model leverages transfer learning and data augmentation techniques for faster and more adequate model training. Lung segmentation is applied to enhance the model performance further. We conducted a pre-trained network comparison with the highest classification performance (F1-Score: 98%) using the ResNet model.

COVID-19: vaccination vs. hospitalization.

OBJECTIVE: Vaccination is the most efficient way to control the coronavirus disease 2019 (COVID-19) pandemic, but vaccination rates remain below the target level in most countries. This multicenter study aimed to evaluate the vaccination status of hospitalized patients and compare two different booster vaccine protocols. SETTING: Inoculation in Turkey began in mid-January 2021. Sinovac was the only available vaccine until April 2021, when BioNTech was added. At the beginning of July 2021, the government offered a third booster dose to healthcare workers and people aged > 50 years who had received the two doses of Sinovac. Of the participants who received a booster, most chose BioNTech as the third dose. METHODS: We collected data from 25 hospitals in 16 cities. Patients hospitalized between August 1 and 10, 2021, were included and categorized into eight groups according to their vaccination status. RESULTS: We identified 1401 patients, of which 529 (37.7%) were admitted to intensive care units. Nearly half (47.8%) of the patients were not vaccinated, and those with two doses of Sinovac formed the second largest group (32.9%). Hospitalizations were lower in the group which received 2 doses of Sinovac and a booster dose of BioNTech than in the group which received 3 doses of Sinovac. CONCLUSION: Effective vaccinations decreased COVID-19-related hospitalizations. The efficacy after two doses of Sinovac may decrease over time; however, it may be enhanced by adding a booster dose. Moreover, unvaccinated patients may be persuaded to undergo vaccination.

COVID-19 Pandemic and the Global Perspective of Turkish Thoracic Society.

It has been more than 3 months now since the first case of COVID-19 was reported in Turkey. Globally, the number of confirmed cases and deaths reached 9,653,048 and 491,128 respectively, as reported by 216 countries by June 27, 2020. Turkey had 1,396 new cases, 194,511 total cases, and 5,065 deaths by the same date. From the first case until today, the Turkish Thoracic Society (TTS) has been very proactive in educating doctors, increasing public awareness, undertaking academic studies, and assisting with public health policies. In the present report, social, academic, and management perspectives of the pandemic are presented under appropriate subtitles. During this critical public health crisis, TTS has once again demonstrated its readiness and constructive stance by supporting public health, healthcare workers, and the environment. This review summarizes the perspective of TTS on each aspect of the COVID-19 pandemic and casts light on its contributions.