To study the prevalence of latent tuberculosis infection among medical students

Background: Risk of developing latent tuberculosis infection increases in medical students with their higher exposure to TB care facilities. Objective: To study the prevalence of latent TB infection among students attending professional degrees MBBS, BDS, MD, MS, MDS at King George’s Medical University, India. Methods: This study was carried out with Tuberculin skin testing among students and active TB cases were excluded. A standard dose of 0.1?mL of purified protein derivative was slowly injected intra dermally into non-dominant forearm. After 48-72 hours, the reaction was estimated by measuring the transverse diameter of the induration. Results: Total 561 students had given consent to get enrolled. Prevalence of latent tuberculosis infection was significant with period of clinical exposure (p-value < 0.05), average size of induration (p-value < 0.001), and history of prior Tuberculin Skin Test (p-value < 0.001). However it was not significant with the age (p-value > 0.05), gender (p-value > 0.05), and history of contact with active cases of TB (p-value > 0.05). Conclusion: The prevalence of latent tuberculosis infection is higher in post graduate students followed by interns and final year students due to more exposure to patients in wards and clinics at King George’s Medical University, India

A Parameter Based Comparative Study of Deep Learning Algorithms for Stock Price Prediction

Stock exchanges are places where buyers and sellers meet to trade shares in public companies. Stock exchanges encourage investment. Companies can grow, expand, and generate jobs in the economy by raising cash. These investments play a crucial role in promoting trade, economic expansion, and prosperity. We compare the three well-known deep learning algorithms, LSTM, GRU, and CNN, in this work. Our goal is to provide a thorough study of each algorithm and identify the best strategy when taking into account elements like accuracy, memory utilization, interpretability, and more. To do this, we recommend the usage of hybrid models, which combine the advantages of the various methods while also evaluating the performance of each approach separately. Aim of research is to investigate model with the highest accuracy and the best outcomes with respect to stock price prediction