Comparative study of Deep Learning Models for Covid 19 Diagnosis

The Covid 19 pandemic that started a couple of years ago has had a devastating effect on mankind across the globe. The disease had no known treatment. Early detection and prevention was very important to curtail the effects of the Pandemic. In this work two deep learning models the RestNet and the models are proposed for diagnosing Corona from chest X-rays and CT scans. The models were trained with publicly available data sets of covid and non covid images. It has been found that Inception V3 performs better than ResNet for chest x-rays and RestNet performs better for CT Scans. The performance of the RestNet is found to be similar for both the chest x-rays and CT scans datasets. © 2023 IEEE.

Sentiment analysis of Covid 19 Vaccines using Twitter Data

Sentiment Analysis is an approach for identifying the polarity of the text. In recent times Social Media is a popular platform for people to socialize and express their opinions on various topics. Given the Covid situation around the globe Social media is facilitating most of the social interactions among paople. In the last two years the most popular topic of discussion has been covid related topics. People have been discussing on various aspects of covid like infections, lockdowns etc. When the vaccines were rolled out by many nations, vaccinations became the hot topic. All the social media platforms like face book and Twitter were flooded with messages related to corona vaccines. The data sets used for analysis in this work specifically belong to the vaccines rolled out by two countries India and USA. TextBlob was used for analysing the sentiments. The results are presented in form of polarity and subjectivity scores and also wordclouds. © 2022 IEEE.

Time series Covid 19 Predictions with Machine Learning Models

The year 2020 began with the outbreak of covid-19 Pandemic, it originated in China and very quickly spread to all the other parts of the world. The deadly virus badly affected the health and economy of Mankind. This work aims to build Machine learning models to predict the spread of Covid-19. The up to date Time series data set of Covid 19 is used in the analytics. Three prediction models namely Regression, SVM and FBProphet are implemented. The results obtained from these models are investigated. FBProphet gives promising results as compared to the other models. The trend and seasonality components of FBProphet are shown to be very useful in the analysis of Time Series Data. © 2021 IEEE.