Sentiment Analysis of COVID-19 Tweets

Sentiment analysis is the field of computer science that studies people's behaviour or attitude towards objects, events, organizations, and products. Organizations make use of this to improve their products. This paper aims to study people's behaviour towards COVID 19. We have taken data from Twitter to analyse the sentiments. The results show that people don't have positive sentiments towards this coronavirus. © 2022 IEEE.

Anti-inflammatory Effects of Different Dietary Antioxidants

Chronic inflammation and oxidative damage have been proven as fundamental factors associated with many systemic diseases, leading to increased morbidity. To deal with this, formulation of new functional foods, dietary polyphenols, and supplements containing multiple natural antioxidants and/or anti-inflammatory agents is required to reduce oxidative stress and inflammatory cascade. Several studies have shown a positive association between increased intake of dietary antioxidants and reduced risk for chronic inflammatory diseases and oxidative stress. This chapter concentrates on the underlying mechanisms of how different groups of dietary antioxidants, like vitamin C, vitamin E, flavonoids, carotenoids, and plant polyphenols, prevent the processes of inflammation and oxidative stress responses. Oxidative stress and inflammation mechanisms are discussed in the light of critical balance of pro- and anti-inflammatory cytokines. Also, roles of dietary antioxidants were discussed as an adjunctive treatment strategy to COVID-19 patients. Given the convincing evidence for protective as well as curative role of dietary antioxidants in inflammatory processes, more detailed understanding on the effects of nutrients on multiple aspects and development of novel anti-inflammatory agents is required to optimize approaches. To improve the bioavailability and targeted delivery of external antioxidants, nonreactive carriers or vehicles are needed to be designed with more precision and accuracy. © 2022, Springer Nature Switzerland AG.

Fuzzy Time-Series Models Based on Intuitionistic Fuzzy, Rough Set Fuzzy, and Differential Evolution

Time-series forecasting is a vital concern for any data having temporal variations. Comparing with the other conventional time-series methodologies, the fuzzy time-series (FTS) proved its superiority. Substantial research using time-series forecasting to predict the stock index data has been found in the earlier works. The fuzzy sets approach alone cannot explain the data thoroughly. In this article, we have proposed three different methods of time-series forecasting. The first method is based on a rough set of FTS, a rule induction-based method;the second method is based on intuitionistic FTS. The last method is the extension of the second method using differential evolution. In the first model, a fuzzy algorithm based on rules is used to derive prediction rules from the time-series data and adopt an adaptive expectation model that replaces the fuzzy logical relationships or groups. In the second method, to split the universe of discourse into a non-uniform interval, a clustering algorithm-based intuitionistic fuzzy approach is used, taking care of the membership and non-membership function. Finally, the last method has been tuned for a better outcome using differential evolution. To examine the results, contrast analyses on the Taiwan stock exchange data and daily cases of COVID-19 pandemic prediction have been carried out. The outcome of the proposed approaches validates that the first and second techniques, showing promising results. However, the third method outperforms the other methods and the present techniques concerning the root-mean-square error metric. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Development of a cognitive-based smartphone application for Malaysian Parkinson’s disease patients: Exploring the possibility?

The COVID-19 pandemic has accelerated the digital health system. Healthcare organizations want to give medical treatment to individuals who live a great distance away. As a result, they are emphasizing the creation of bespoke telemedicine apps. The number of individuals using telemedicine apps is increasing significantly. Increasing technology gives patients healthcare resources. This has been made feasible via a new telemedicine system and by developing a telemedicine app. Patients can use several technologies to communicate with healthcare professionals. For comfort and privacy, you can employ live visual media. The creation of telemedicine apps is the most attractive and practical investment. With the growing availability and usage of technology in PD, the focus of these technologies is gradually turning toward the disease's vast spectrum of Non-Motor Symptoms (NMS). The nature of NMS makes them difficult to objectively measure, further development and building on experience gained in other conditions may still result in NMS capture that is feasible. Although it is impossible to offer recommendations for the use of digital technology outcomes for NMS in clinical practise based on currently available data, evidence for these devices is evolving, and such guidance may become accessible in the not-too-distant future. To our knowledge, this is the first telemedicine method of its sort to address cognition as one of the NMS in Malay PD patients. The project will be done on two consecutive phases (1 year each);Phase1 aims to develop the Dementia Coach Mobile App, and Phase2 aims to validation of this app by using PD patients sample from SASMEC. Therefore, we hypothesize that developing a friendly mobile app to assess dementia for PD patients is highly beneficial and could be used for diagnosis of NMS in PD patients. © 2022 by Mohamed et al.

The prevalence, preventive measures and economic impact of pandemic COVID-19 in India: The initial phase

The novel coronavirus (SARS-CoV-2) is posing a serious threat to the mankind with its massive infection rate and potentially fatality. A total of 212 countries have been infected within the 112 days of first report causing 2 314 621 confirmed cases and 157 847 deaths worldwide. India, the country which is already battling with poverty, malnutrition and high population density is also at the second stage of coronavirus transmission. The situation is worsening and the attention has focused on the prevalence and preventive measures to be taken to protect 1.35 billion people of the largest democratic country of the world. In this review, a study has been designed to evaluate the prevalence, transmission, clinical symptoms, and preventive measures to control the community transmission of this fatal disease. The initial impact of coronavirus disease (COVID-19) outbreak on Indian economy has also been dealt with. This study reviews and summarizes the main points of the epidemic in India until the end of April 2020.

COVID-19 Stroke Apical Lung Examination Study: A Diagnostic and Prognostic Imaging Biomarker in Suspected Acute Stroke.

BACKGROUND AND PURPOSE: Diagnosis of coronavirus disease 2019 (COVID-19) relies on clinical features and reverse-transcriptase polymerase chain reaction testing, but the sensitivity is limited. Carotid CTA is a routine acute stroke investigation and includes the lung apices. We evaluated CTA as a potential COVID-19 diagnostic imaging biomarker. MATERIALS AND METHODS: This was a multicenter, retrospective study (n = 225) including CTAs of patients with suspected acute stroke from 3 hyperacute stroke units (March-April 2020). We evaluated the reliability and accuracy of candidate diagnostic imaging biomarkers. Demographics, clinical features, and risk factors for COVID-19 and stroke were analyzed using univariate and multivariate statistics. RESULTS: Apical ground-glass opacification was present in 22.2% (50/225) of patients. Ground-glass opacification had high interrater reliability (Fleiss κ = 0.81; 95% CI, 0.68-0.95) and, compared with reverse-transcriptase polymerase chain reaction, had good diagnostic performance (sensitivity, 75% [95% CI, 56-87]; specificity, 81% [95% CI, 71-88]; OR = 11.65 [95% CI, 4.14-32.78]; P < .001) on multivariate analysis. In contrast, all other contemporaneous demographic, clinical, and imaging features available at CTA were not diagnostic for COVID-19. The presence of apical ground-glass opacification was an independent predictor of increased 30-day mortality (18.0% versus 5.7%, P = .017; hazard ratio = 3.51; 95% CI, 1.42-8.66; P = .006). CONCLUSIONS: We identified a simple, reliable, and accurate COVID-19 diagnostic and prognostic imaging biomarker obtained from CTA lung apices: the presence or absence of ground-glass opacification. Our findings have important implications in the management of patients presenting with suspected stroke through early identification of COVID-19 and the subsequent limitation of disease transmission.