Real-Time Twitter Spam Detection and Sentiment Analysis using Machine Learning and Deep Learning Techniques.

In this modern world, we are accustomed to a constant stream of data. Major social media sites like Twitter, Facebook, or Quora face a huge dilemma as a lot of these sites fall victim to spam accounts. These accounts are made to trap unsuspecting genuine users by making them click on malicious links or keep posting redundant posts by using bots.

Screening COVID-19 Patients Using Safe Practice Score System in Non-COVID Radiology Departments.

Background: A prospective study was designed to evaluate the role of safe practice score system (SPSS) for targeted screening of patients in the non-COVID radiology department with the objective to (a) determine the incidence of COVID-19 in patients visiting non-COVID facilities, (b) to determine the sensitivity and specificity with predictive value of SPSS system to identify high-risk COVID patients undergoing ultrasound and echocardiographic examinations, (c) determination of relative risk (RR) estimation for health-care staff and other visiting patients and attendants, and (d) overall impact of the use of SPSS in the prevention of spread of the disease in the society.

Methods: The study comprised a cohort of 688 patients who initially presented as non-COVID patients for ultrasound and echocardiography tests to a non-COVID health-care facility. Patients were divided into low-, moderate-, and high-risk COVID-19 probability groups based on SPSS screening scores of 0-3, 4-6, and more than 6, respectively.

Socio-demographic trends in ocular cysticercosis.

There has been a gradual change in the socio-demographic trends of ocular/adnexal cysticerosis. We present the results of a 5-year study of 33 cases of ocular/adnexal cysticercosis and compare our observations with those reported by previous authors. The male:female ratio in our study was 2:1 and maximum number of patients (45%) belonged to the age-group of 31-40 years.