Machine Learning Approaches in Deal with the COVID-19, Comprehensive Study

The novel Covid illness (COVID-19) has spread more than 219 nations on the globe as a pandemic, making disturbing impacts on medical care, financial conditions, and global connections. The primary goal of the review is to give the Artificial Intelligence's technological aspect and other applicable innovations and their suggestions for standing up to COVID-19 and prevention of the pandemic's frightful impacts. This article presents various approaches with AI moves toward that have huge contribution in the medical service fields, then, at that point, features and sorts their applications in facing Corona virus, like identification and finding, information examination and treatment methods, exploration and medication improvement, social control and benefits, and the expectation of outbreaks. The review tends to the connection between the innovations and the pandemics just as the expected effects of innovation in medical care with the presentation of AI and normal language processing devices. It is usual that this exhaustive review will uphold specialists in demonstrating medical services frameworks and drive further investigations in cutting edge innovations. At last, we conclude that enticing simulated artificial intelligence techniques, probabilistic models, as well as supervised learning are needed to handle future pandemic difficulties. © The Electrochemical Society

Secure Data Sharing of Electronic Health Record (EHR) on the Cloud Using Blockchain in Covid-19 Scenario

In the current scenario of Covid-19, health data are stored in a centralized server at hospitals and medical institutions, which is susceptible to diverse extortions, such as malicious tinkering, patient data loss, and natural disasters. The advent of blockchain expertise fetches a new-fangled notion to decipher the abovementioned security issues due to its features of immutability, verifiability, and decentralization. This technology was initially invented for money-associated exchanges and financial transactions using centralized authorities. Nowadays, the popularity of blockchain technology is increasing enormously in the field of healthcare. Healthcare devices having a great utilization in the field of healthcare, but they pose several privacy and security threats to the sensitive data of a patient. To overcome these issues, we have proposed a novel hybrid system that combines the merits of centralized and decentralized blockchain for the secure sharing of health data between health devices and hospitals. The proposed system will be useful in the context of protected, interoperable, and effectual admittance to health registers by patients, hospitals, and third revelries while maintaining the privacy of patients’ penetrating data. Also, we used smart contracts in an Ethereum-based blockchain for access control. Ethereum is a programmable blockchain platform that utilizes the strong environment of solidity (a state-based scripting language). By using both centralized and decentralized properties of blockchain together, we can effectively secure the patient's sensitive data. The data of a patient generated by heterogeneous devices would be shared in a secured manner. We have analyzed that the proposed system is better than the existing systems in terms of scalability, data ownership, and interoperability. The deployment cost of the proposed hybrid model may be the limitation. In the forthcoming, we would implement the suggested hybrid exemplary to advance the security of health data. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Correlation between HRCT Findings of Symptomatic COVID-19 Patient with RT-PCR Test in a Tertiary Hospital of Bangladesh

The COVID-19 pandemic has turned into a global calamity and affected millions of lives around the world. Even though the vaccination efforts have started, they are yet to have an effective impact on the lower to middle-income countries. Early detection and isolation are still the best way to control the spread of the virus. The standard practice for detecting COVID-19 is the RT-PCR (Reverse Transcription Polymerase Chain Reaction) test but this test has a high probability of producing false-negative results plus lack of availability at all the time due to shortage of kit. Since COVID-19 is a respiratory disease affecting the lungs and the imaging patterns caused by COVID-19 can be observed in chest HRCT (High Resolution Computed Tomography) scans. As a result, HRCT can be used as an alternative diagnostic modality for any suspected cases of COVID-19. In this cross-sectional study was carried out in the Department of Radiology and Imaging, BSMMU, Dhaka, Bangladesh from May 12, 2020 to August 10, 2020. Chest HRCT scans of 284 suspected patients irrespective of age and sex who had done RT-PCR test either positive or negative test result having symptoms suggesting COVID pneumonia were enrolled in this study. Patients who had not done RT-PCR and who were not willing to do HRCT chest were excluded. According to the study, ground glass opacity is the most common feature and found in 89.44% of patients. The other predominant features were including consolidation, crazy paving, fibrotic density and vascular enlargement. The diagnostic performance of the CT scan was also evaluated using the RT-PCR test result as the gold standard and the sensitivity, specificity, and accuracy of the CT scan diagnosis were found to be 83.2%, 50% and 79.9% respectively. The severity of the five lung lobes has also been studied. The right middle lobe and the left upper lobe seemed to be in more severe condition for most of the patients compared to the other lung lobes.

SARS-CoV-2 Detection in Gingival Crevicular Fluid.

Understanding the pathophysiology of the coronavirus disease 2019 (COVID-19) infection remains a significant challenge of our times. The gingival crevicular fluid being representative of systemic status and having a proven track record of detecting viruses and biomarkers forms a logical basis for evaluating the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The study aimed to assess gingival crevicular fluid (GCF) for evidence of SARS-CoV-2 in 33 patients who were deemed to be COVID-19 positive upon nasopharyngeal sampling. An attempt was also made to comparatively evaluate it with saliva in terms of its sensitivity, as a diagnostic fluid for SARS-CoV-2. GCF and saliva samples were collected from 33 COVID-19-confirmed patients. Total RNA was extracted using NucliSENS easyMAG (bioMérieux) and eluted in the elution buffer. Envelope gene (E gene) of SARS-CoV-2 and human RNase P gene as internal control were detected in GCF samples by using the TRUPCR SARS-CoV-2 RT qPCR kit V-2.0 (I) in an Applied Biosystems 7500 real-time machine. A significant majority of both asymptomatic and mildly symptomatic patients exhibited the presence of the novel coronavirus in their GCF samples. Considering the presence of SARS-CoV-2 RNA in the nasopharyngeal swab sampling as gold standard, the sensitivity of GCF and saliva, respectively, was 63.64% (confidence interval [CI], 45.1% to 79.60%) and 64.52% (CI, 45.37% to 80.77%). GCF was found to be comparable to saliva in terms of its sensitivity to detect SARS-CoV-2. Saliva samples tested positive in 3 of the 12 patients whose GCF tested negative, and likewise GCF tested positive for 2 of the 11 patients whose saliva tested negative on real-time reverse transcription polymerase chain reaction. The results establish GCF as a possible mode of transmission of SARS-CoV-2, which is the first such report in the literature, and also provide the first quantifiable evidence pointing toward a link between the COVID-19 infection and oral health.