Sentiment Analysis on COVID-19 Tweets

The global proliferation of COVID-19, as well as the growth of platforms as a primary source of information for many individuals, has elicited a wide spectrum of reactions. However, keeping up with this mass scenario is difficult. A large number of people offer their opinions and perspectives on current events on social media, making it difficult for a human to read and comprehend everything. Tweets disseminate a great deal of information. Using public Twitter comments, our study attempted to conduct a sentiment analysis of the entire discourse about COVID-19 in a paper. We improved on earlier methodologies and methods for sentiment analysis. Our primary goal is to examine tweets concerning COVID-19 from the previous year using natural language processing and neural network methods. We used a multiclass dataset and applied it to BOW, TFIDF, and One Hot Encoding. Furthermore, after training four distinct classifiers with these different pre-processing algorithms in each classifier, we performed a competitive analysis and found RoBERTa as the best performing with 90% accuracy. © 2022 IEEE.

Reduced Duration Intracavitary Brachytherapy in Cervix Malignancies: A Comparative Analysis from Single Institute

Purpose: The on-going pandemic has impacted the use of anesthesia and the operating room frequency thereby affecting the brachytherapy treatment in various institutions due to the COVID-19 protocols. This has led to single applications of Intracavitary brachytherapy (ICRT) being used to deliver entire treatment boost in cervix cancer. We present our dosimetric and early clinical outcomes comparing traditional weekly three-fractions ICRT with single application/ two-applications ICRT Material(s) and Method(s): In this retrospective analysis conducted in our department, a total of 39 cases, treated between January 2021 to January 2022 were evaluated for the study. Of these, 15 cases were treated with the traditional once a week applicator insertion for 3 fractions and 24 cases underwent lesser application - 20 cases underwent 2 insertions and 4 cases single insertion (all receiving total 3 fractions of 7Gy each). The dosimetric parameters were compared including CTV D90 and D95 along with rectum, sigmoid and bladder D2cc, 1cc and 0.1cc respectively. The acute toxicity assessment was done using the RTOG scale. The follow-up was undertaken as per the institutional protocol and Mann-Whitney U-test were applied to compare the cohorts. Result(s): With a median follow-up of 6 months, the median CTV was D90%: 81.2 vs. 80.9 Gy and the median CTV volume was 44.3 vs 42.9 cc respectively. The 0.1 cm3 and 2 cm3 to bladder, rectum, and sigmoid were 105.6 vs 104.2 Gy and 85.5 vs 85.9Gy, 89.4Gy vs 88.7Gy and 69.1 vs 67.8Gy, and 84.7 vs 84.1Gy and 71.7 vs 69.9Gy, respectively suggesting no significant difference in the dosimetric outcomes with the two forms of applications. The less than three applications had a shorter overall treatment time with median OTT of 43 days vs. 55 days (p = 0.02). On completion of treatment and 6 months follow-up, local control was achieved in all patients. There was no significant difference in the acute toxicities in terms of cystitis and proctitis in both forms of the application. Conclusion(s): The single application/ twice application ICRT procedure showed similar outcomes as the traditional three-week duration treatment in terms of dosimetric outcomes and acute toxicities and ultimately leading to shortened overall treatment time. It also helped reduce the anesthesia burden and various resources associated with the procedure. Copyright © 2022

PO43 Presentation Time: 4:45 PM: Reduced Duration Intracavitary Brachytherapy in Cervix Malignancies: A Comparative Analysis from Single Institute

Purpose: The on-going pandemic has impacted the use of anesthesia and the operating room frequency thereby affecting the brachytherapy treatment in various institutions due to the COVID-19 protocols. This has led to single applications of Intracavitary brachytherapy (ICRT) being used to deliver entire treatment boost in cervix cancer. We present our dosimetric and early clinical outcomes comparing traditional weekly three-fractions ICRT with single application/ two-applications ICRT Materials and Methods: In this retrospective analysis conducted in our department, a total of 39 cases, treated between January 2021 to January 2022 were evaluated for the study. Of these, 15 cases were treated with the traditional once a week applicator insertion for 3 fractions and 24 cases underwent lesser application - 20 cases underwent 2 insertions and 4 cases single insertion (all receiving total 3 fractions of 7Gy each). The dosimetric parameters were compared including CTV D90 and D95 along with rectum, sigmoid and bladder D2cc, 1cc and 0.1cc respectively. The acute toxicity assessment was done using the RTOG scale. The follow-up was undertaken as per the institutional protocol and Mann-Whitney U-test were applied to compare the cohorts. Results: With a median follow-up of 6 months, the median CTV was D90%: 81.2 vs. 80.9 Gy and the median CTV volume was 44.3 vs 42.9 cc respectively. The 0.1 cm3 and 2 cm3 to bladder, rectum, and sigmoid were 105.6 vs 104.2 Gy and 85.5 vs 85.9Gy, 89.4Gy vs 88.7Gy and 69.1 vs 67.8Gy, and 84.7 vs 84.1Gy and 71.7 vs 69.9Gy, respectively suggesting no significant difference in the dosimetric outcomes with the two forms of applications. The less than three applications had a shorter overall treatment time with median OTT of 43 days vs. 55 days (p = 0.02). On completion of treatment and 6 months follow-up, local control was achieved in all patients. There was no significant difference in the acute toxicities in terms of cystitis and proctitis in both forms of the application. Conclusion: The single application/ twice application ICRT procedure showed similar outcomes as the traditional three-week duration treatment in terms of dosimetric outcomes and acute toxicities and ultimately leading to shortened overall treatment time. It also helped reduce the anesthesia burden and various resources associated with the procedure.

Digital platform to defeat COVID-19

This review discusses some of the possible technological concepts and their role to fight against COVID-19, which could possibly help to control the outbreak. The use of quantum computers, machine learning, facial recognition, satellite technology, robots, health sensory and mobile apps for monitoring and gathering sufficient quality data are covered.

Telephone clinic outcomes during the coronavirus disease 2019 pandemic: results from an ENT department.

OBJECTIVE: To study the impact of telemedicine on patient outcomes during a nationwide lockdown to halt the spread of coronavirus disease 2019. METHODS: A retrospective study was conducted to examine telemedicine consultations of newly referred patients over 7 days during a national lockdown. Overall outcomes of telephone clinics were recorded, measured as either patient discharged, imaging requested, patient referred to another specialty, further telephone follow up required, patient initiated follow up or face-to-face appointment required. RESULTS: Data were collected from 104 patients. Outcomes showed that 17 patients were discharged, 15 had imaging requested, 11 were referred to another specialty, 11 had further telemedicine appointments, 31 had patient-initiated follow up and 19 received face-to-face appointments. Overall, 57 per cent of patients avoided hospital visits and 17 per cent required face-to-face appointments. Of higher risk patients, 49 per cent were managed remotely. After eight months, no significant morbidity or mortality was reported. CONCLUSION: Almost half of the higher risk patients avoided a hospital visit. The majority of patients were managed remotely, and thus the risk and spread of infection were reduced. Telemedicine has an important role in ENT out-patients.

3D printing in managing supply disruptions related to COVID-19 pandemic: Food and Drug Administration's current thinking on regulation

Recent developments and collaborations of pharmaceutical manufacturers, hospitals, and government funded research bodies using 3D printing technology have been highlighted for the management of the healthcare crisis. 3D printing is a process of converting virtual 3D models developed by computer aided design into physical forms upon addition of material layer-by-layer (also known as additive manufacturing). This 3D printing is supposed to revolutionize significantly the healthcare system in the coming years. This process involves a tailored deposition of biomaterials layer by layer such as polylactic acid (PLA), polyvinyl alcohol (PVA), or other suitable pharma-grade polymers, copolymers, and their combinations to formulate three-dimensional custom designs with controlled architecture and composition. Food and Drug Administration (FDA) is currently thinking on regulation to ease the import restrictions for products intended for the detection and diagnosis of COVID-19 to ensure the timely availability of test kits.

Developmental biology of Corona vaccine: Lipid nanoparticle mRNA-encapsulation, a safe approach

The global pandemic of COVID-19 is progressing rapidly across the world and declared as health emergency. The novel Coronavirus can cause severe lower respiratory tract infections primarily in geriatric, immunocompromised persons, infants and patients with comorbidities, or genetic disorders. Few Emergency Use Authorizations (EAUs) have been granted by FDA and other regulatory bodies with an aim to repurpose the existing approved medicines to fight the disease, and till date no specific treatment methodologies or preventive measures are available. At present, numerous medications which are already approved for other therapeutic indications, as well as the new medications, are undergoing clinical trials for the evaluation of safety and efficacy against COVID-19 infection. These therapeutic ranges include antimalarial, antiviral, steroids, convalescent plasma containing antibodies, and immune modulators, etc. Nevertheless, the primary focus is on preventive care and currently more than hundred potential vaccine candidates are under development by leading biotech companies across the globe which are at different phases of clinical development. Lipid based mRNA delivery, DNA delivery and mAbs are the most advanced technologies being embraced besides whole-virion inactivated vaccine, attenuated live vaccine, non-replicating viral vector-based vaccine, protein single unit vaccine and multiunit vaccine. This review focuses on the current progress in drug delivery systems of COVID-19 vaccine across industries, academics, and government funded research institutes with a special focus on the synthetic mRNA-based lipid nanoparticle (LNP).

A Best Effort Classification Model For Sars-Cov-2 Carriers Using Random Forest

The whole world now is dealing with Coronavirus, and it has turned to be one of the most widespread and long-lived pandemics of our times. Reports reveal that the infectious disease has taken toll of the almost 80% of the world's population. Amidst a lot of research going on with regards to the prediction on growth and transmission through Symptomatic carriers of the virus, it can't be ignored that pre-symptomatic and asymptomatic carriers also play a crucial role in spreading the reach of the virus. Classification Algorithm has been widely used to classify different types of COVID-19 carriers ranging from simple feature-based classification to Convolutional Neural Networks (CNNs). This research paper aims to present a novel technique using a Random Forest Machine learning algorithm with hyper-parameter tuning to classify different types COVID-19-carriers such that these carriers can be accurately characterized and hence dealt timely to contain the spread of the virus. The main idea for selecting Random Forest is that it works on the powerful concept of "the wisdom of crowd" which produces ensemble prediction. The results are quite convincing and the model records an accuracy score of 99.72%. The results have been compared with the same dataset being subjected to K-Nearest Neighbour, logistic regression, support vector machine (SVM), and Decision Tree algorithms where the accuracy score has been recorded as 78.58%, 70.11%, 70.385,99% respectively, thus establishing the concreteness and suitability of our approach.

A regression model frame with IoT to predict COVID zone

In this paper, we are planning to build an application through which victims of Covid-19 can put their data. Once an effective data set is built, the application is capable to predict a COVID-19 zone based on these data by using a regression model. The parameters of the data set will be: 1. How many times a person visited outside. 2. City of the person, who visited abroad recently if yes then which country (take the ratio of victims to their population density as a parameter), if no then we will put a zero. 3. The cases in their home town by simply accessing their location (take the ratio of victims to the population density of that area). 4. Once data set is built, then train a regression model to predict the chances of a person being a victim of Covid - 19 and once that information is available we can simply observe in which area the no of suspected no of people is greater through which we can tell the chance of an area being affected by this situation. 5. Although parameters of the data set are limited now but we are planning to add more so that more accurate models can be built. © 2021 Institute of Physics Publishing. All rights reserved.