The world is reworking in a digital era. However, the field of medicine was quite repulsive to technology. Recently, the advent of newer technologies like machine learning has catalyzed its adoption into healthcare. The blending of technology and medicine is facilitating a wealth of innovation that continues to improve lives. With the realm of possibility, machine learning is discovering various trends in a dataset and it is globally practiced in various medical conditions to predict the results, diagnose, analyze, treat, and recover. Machine Learning is aiding a lot to fight the battle against Covid-19. For instance, a face scanner that uses ML is used to detect whether a person has a fever or not. Similarly, the data from wearable technology like Apple Watch and Fitbit can be used to detect the changes in resting heart rate patterns which help in detecting coronavirus. According to a study by the Hindustan Times, the number of cases is rapidly increasing. Careful risk assessments should identify hotspots and clusters, and continued efforts should be made to further strengthen capacities to respond, especially at sub-national levels. The core public health measures for the Covid-19 response remain, rapidly detect, test, isolate, treat, and trace all contacts. The work presented in this paper represents the system that predicts the number of coronavirus cases in the upcoming days as well as the possibility of the infection in a particular person based on the symptoms. The work focuses on Linear Regression and SVM models for predicting the curve of active cases. SVM is least affected by noisy data, and it is not prone to overfitting. To diagnose a person our application has a certain question that needs to be answered. Based on this, the KNN model provides the maximum likelihood result of a person being infected or not. Tracking and monitoring in the course of such pandemic help us to be prepared.

The coronavirus disease 2019 (COVID-19) pandemic, which originated in Wuhan, China, has now affected more than 100 countries around the world. In the light of the WHO declaring COVID-19 as a public health emergency of international concern, despite global efforts to contain the killer disease, the cases are still increasing due to community spread. Coronavirus or the severe acute respiratory syndrome coronavirus 2 is present abundantly in the infected person's salivary and nasopharyngeal secretions. The contagion occurs very easily through these droplets, which are very evident in any dental clinic. However, the dental clinics are open for emergency treatments. The aim of this article is to give a glance into the impact of COVID-19 on dentistry in India.

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BACKGROUND During the lockdown period of COVID-19 pandemic, dental colleges in Bangalore, India, had switched to online dental education and when the cases started to decline, the dental colleges finally welcomed students on campus in November 2020 following the Government directions. Majority of the dental procedures produce droplets and aerosols in a dental practice. In this context, the standard protective measures are not enough in the daily dental practice during this pandemic. Dental professionals, students in particular should be aware of the main symptoms of COVID-19, its mode of transmission and precautions to be adopted in the dental practice so as to break the chain of infection. The purpose of the study was to investigate the perception regarding COVID-19 among the dental students of a dental teaching institution in Bangalore city. METHODS An online questionnaire was created to assess the perception about COVID-19 among dental students. Total enumeration method was followed, and undergraduates, interns and post graduate students of a tertiary care dental hospital participated in the online survey. chi-square goodness of fit test was used to compare the differences in the distribution of respondents and independent chi- square test was used to do the comparison in the difference of responses towards the study questionnaire between the students studying in different undergraduate years; with level of significance set at P < 0.05. RESULTS About 380 dental students participated in the online survey; correct response rate was slightly higher among clinical dental students than pre-clinical students. Educational and training programmes related to COVID-19, infection control and practices were implemented at the institution for the dental professionals in the academic level. CONCLUSIONS The perception about COVID-19 among pre-clinical dental students were slightly lower than the clinical students. KEY WORDS Clinical, COVID-19, Dental Students, Pre-Clinical