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Abstract: Artificial intelligence (AI) has proven time and time again to be a game-changer innovation in every walk of life, including medicine. Introduced by Dr. Gunn in 1976 to accurately diagnose acute abdominal pain and list potential differentials, AI has since come a long way. In particular, AI has been aiding in radiological diagnoses with good sensitivity and specificity by using machine learning algorithms. With the coronavirus disease 2019 pandemic, AI has proven to be more than just a tool to facilitate healthcare workers in decision making and limiting physician-patient contact during the pandemic. It has guided governments and key policymakers in formulating and implementing laws, such as lockdowns and travel restrictions, to curb the spread of this viral disease. This has been made possible by the use of social media to map severe acute respiratory syndrome coronavirus 2 hotspots, laying the basis of the "smart lockdown" strategy that has been adopted globally. However, these benefits might be accompanied with concerns regarding privacy and unconsented surveillance, necessitating authorities to develop sincere and ethical government-public relations., (Copyright © 2022 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license.)

Background: Due to the Novel Coronavirus Disease, medical education has transformed from a physical to an online-medium. The importance of physical education in low-and-middle-income countries (LMICs), where online education can be challenging there is a need to explore the factors that affect online education. This study assesses the perspective and mental health of students whose medical education has been impacted by the pandemic., Methods: An online-questionnaire was distributed through social media platforms from October-to-December 2020 through Google-Forms among medical students across Pakistan. Two grading-scales were used to score anxiety and depression. Descriptive statistics and a logistic regression analysis were used to identify factors associated with anxiety and depression among medical students. p<0.05 was considered as significant. Data was analyzed using STATA v.15., Results: Total of 433 medical students participated in the study where 68.1% had some form of depression and 10.9% had anxiety. Around 65%-participants disagreed with the preference for online-classes. Seventy percent agreed on "Has the thought of the pandemic made you worry about your academic future" being associated with COVID-19 related-depression (OR: 2.03, 95%CI: 1.32-3.11). Multivariate analysis showed agreeing to "COVID affected my educational performance" was associated with anxiety (OR:1.45, 95%CI: 1.03-2.06) and depression (OR: 1.27, 95%CI: 1.03-1.56)., Conclusions: Being part of the Low- and-Middle-Income Countries (LMIC), online-education itself becomes a challenge. Given the continued shutdown of universities across the country and the growing anxiety and depression amongst the students, adequate measures should be taken to help in coping up with the current challenge.