BACKGROUND: Recent occurrence of the 2019 coronavirus disease (COVID-19) outbreak, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has highlighted the need for fast, accurate, and simple strategies to identify cases on a large scale. OBJECTIVE: This study aims to develop and test an accurate detection and severity classification methodology that may help medical professionals and non-radiologists recognize the behavior and propagation mechanisms of the virus by viewing computed tomography (CT) images of the lungs with implicit materials. METHODS: In this study, the process of detecting the virus began with the deployment of a virtual material inside CT images of the lungs of 128 patients. Virtual material is a hypothetical material that can penetrate the healthy regions in the image by performing sequential numerical measurements to interpret images with high data accuracy. The proposed method also provides a segmented image of only the healthy parts of the lung. RESULTS: The resulting segmented images, which represent healthy parts of the lung, are classified into six levels of severity. These levels are classified according to physical symptoms. The results of the proposed methodology are compared with those of the radiologists’ reports. This comparison revealed that the gold-standard reports correlated with the results of the proposed methodology with a high accuracy rate of 93%. CONCLUSION: The study results indicate the possibility of relying on the proposed methodology for discovering the effects of the SARS-CoV-2 virus in the lungs through CT imaging analysis with limited dependency on radiologists.

Background Coronavirus disease 2019 (COVID-19) is a viral respiratory disease that first emerged in China in December 2019 and quickly spread worldwide. As the prevalence of COVID-19 increases, radiological examination is becoming an essential diagnostic tool for identifying and managing the disease’s progression. Therefore, we aimed to identify the chest imaging features and clinical characteristics of patients with laboratory-confirmed COVID-19 in Saudi Arabia. Material/Methods In this retrospective study, data of laboratory-confirmed COVID-19 patients were collected from 4 hospitals in Jeddah, Saudi Arabia. Their common clinical characteristics, as well as imaging features of chest X-rays and computed tomography (CT) images, were analyzed. Results A total of 297 patients with laboratory-confirmed COVID-19 who underwent chest imaging were investigated in this study. Of these patients, 77.9% were male and 22.2% were female. Their mean age was 48 years old. The most common clinical symptoms were fever (187 patients; 63%) and cough (174 patients; 58.6%). The predominant descriptive chest imaging findings were ground-glass opacities and consolidation. Locations of abnormalities were bilateral, mainly distributed peripherally, in the lower lung zones, and in the middle lung zones. Conclusions This study provides an understanding of the most common clinical and radiological features of patients with laboratory-confirmed COVID-19 in Saudi Arabia. The majority of COVID-19 patients in our study cohort had either stable or worse progression of lung lesions during follow-ups; thus, they presented moderate disease cases. Elderly males were more affected by COVID-19 than females, with fever and cough being the most common clinical symptoms.

This study investigated the strategic planning procedure used by the University of Jeddah to determine which of its efficacy criteria are the most significant for future development. A university's performance is founded on its ability to capitalize on its specialization and set of skills obtained through meticulous planning and development and involves setting goals using analysis tools to compare options and prioritize constructs. Evaluation approaches to strategic planning lack adaptability and durability. Thus, a high-level deductive instrument that aggregates trade-offs and prioritizes the most essential aspects is needed. This study used the Fuzzy Analytical Hierarchical Procedure (FAHP) to examine whether the University of Jeddah's strategy formulation process improves strategy and planning. This study defined the objectives and criteria, established pairwise comparisons based on the owners of the strategic plan and the faculty and administration questionnaire responses, assigned weights to each criterion, verified their consistency, and ranked them in importance order. This study showed that FAHP can help groups make strategic planning decisions in universities.