Sine Cosine Optimization with Deep Learning-Based Applied Linguistics for Sentiment Analysis on COVID-19 Tweets

Applied linguistics is an interdisciplinary domain which identifies, investigates, and offers solutions to language-related real-life problems. The new coronavirus disease, otherwise known as Coronavirus disease (COVID-19), has severely affected the everyday life of people all over the world. Specifically, since there is insufficient access to vaccines and no straight or reliable treatment for coronavirus infection, the country has initiated the appropriate preventive measures (like lockdown, physical separation, and masking) for combating this extremely transmittable disease. So, individuals spent more time on online social media platforms (i.e., Twitter, Facebook, Instagram, LinkedIn, and Reddit) and expressed their thoughts and feelings about coronavirus infection. Twitter has become one of the popular social media platforms and allows anyone to post tweets. This study proposes a sine cosine optimization with bidirectional gated recurrent unit-based senti-ment analysis (SCOBGRU-SA) on COVID-19 tweets. The SCOBGRU-SA technique aimed to detect and classify the various sentiments in Twitter data during the COVID-19 pandemic. The SCOBGRU-SA technique follows data pre-processing and the Fast-Text word embedding process to accomplish this. Moreover, the BGRU model is utilized to recognise and classify sen-timents present in the tweets. Furthermore, the SCO algorithm is exploited for tuning the BGRU method's hyperparameter, which helps attain improved classification performance. The experimental validation of the SCOBGRU-SA technique takes place using a benchmark dataset, and the results signify its promising performance compared to other DL models.

Approach to the Patient With Pituitary Adenoma Using Telemedicine: Knowledge Gaps and Recommendations

Telemedicine (TM) can be defined as the practice of medicine using technology such as video teleconferencing, telephone calls, or emails in order to provide health care from a distance. The emergence of the coronavirus disease 2019 (COVID-19) pandemic and its potential complications have created an urgent need for the transformation of physical visits into virtual encounters. Pituitary adenomas are one of the common endocrine tumors and can manifest with hormonal or mass effects. COVID-19 impacted the common pathway of diagnosis and treatment of these masses. TM utilization for pituitary adenomas has not been addressed thoroughly in the literature despite how common they are. In this review article, we discuss and implement what has been written in the literature about TM for pituitary adenoma alongside our suggested protocol.