Detecting COVID-19 Pneumonia over Fuzzy Image Enhancement on Computed Tomography Images.

COVID-19 is the worst pandemic that has hit the globe in recent history, causing an increase in deaths. As a result of this pandemic, a number of research interests emerged in several fields such as medicine, health informatics, medical imaging, artificial intelligence and social sciences. Lung infection or pneumonia is the regular complication of COVID-19, and Reverse Transcription Polymerase Chain Reaction (RT-PCR) and computed tomography (CT) have played important roles to diagnose the disease. This research proposes an image enhancement method employing fuzzy expected value to improve the quality of the image for the detection of COVID-19 pneumonia. The principal objective of this research is to detect COVID-19 in patients using CT scan images collected from different sources, which include patients suffering from pneumonia and healthy people. The method is based on fuzzy histogram equalization and is organized with the improvement of the image contrast using fuzzy normalized histogram of the image. The effectiveness of the algorithm has been justified over several experiments on different features of CT images of lung for COVID-19 patients, like Ground-Glass Opacity (GGO), crazy paving, and consolidation. Experimental investigations indicate that among the 254 patients, 81.89% had features on both lungs; 9.5% on the left lung; and 10.24% on the right lung. The predominantly affected lobe was the right lower lobe (79.53%).

Assessment of Knowledge, Practice and Attitude about Biomedical Waste Management among Healthcare Professionals during COVID-19 Crises in Al-Ahsa.

Biomedical waste (BMW) management is an essential practice of healthcare professionals (HCPs) for preventing health and also environmental hazards. Coronavirus disease (COVID-19) has become a global pandemic, posing significant challenges for healthcare sectors. A cross-sectional study was performed to assess the knowledge, practice, and attitude on BMW management among HCPs when taking care of patients with COVID-19 and associated with demographic variables. From Al-Ahsa healthcare sectors, 256 HCPs were selected randomly, of which 105 (41%) had excellent knowledge, 87 (34%) had good knowledge, and 64 (25%) had poor knowledge with a mean score of 13.1 ± 3.6. A higher mean score was (14.4 ± 3.2) obtained by physicians, and (13.6 ± 3.8) nurses than the other HCPs. Regarding practice, 72 (28.1%) HCPs used and discarded PPE while handling biomedical wastes. Additionally, 88 (34.4%) followed proper hand hygiene before and after each procedure and whenever needed. Physicians, nurses, and respiratory therapists had a more favorable attitude than other HCPs. There was a statistically significant association found among knowledge level and educational qualification (p < 0.0001), gender (p < 0.001), and work experience (p < 0.05). Emphasis is needed to train all HCPs regarding proper BMW management during this pandemic to prevent infection transmission.