Psychological stress among anesthesia residents during COVID-19 pandemic and how to mitigate them.

The impact of the novel coronavirus disease 19 (COVID-19) has overburdened the anesthesia fraternity both physically and mentally. The academic and training schedule of the medical residents in the last year was also disrupted. Since we are in the early phase of the second peak of the COVID-19 pandemic, it is time to reconsider the causes of stress in anesthesia residents and methods to mitigate them. In this non-systematic review, authors have included articles from PubMed, Medline, and Google scholar with keywords "identify strategies" "preventing and treating psychological disorders," and "medical students" from year 2010 onwards were included. Apart from these keywords, we have included the coping strategies and early psychiatric consultation methods. This review article aims at early identification, workplace environment changes, and implementation of early coping strategies in anesthesia residents during this second peak of COVID-19.

Artificial Intelligence and technology in COVID Era: A narrative review.

Application of artificial intelligence (AI) in the medical field during the coronavirus disease 2019 (COVID-19) era is being explored further due to its beneficial aspects such as self-reported data analysis, X-ray interpretation, computed tomography (CT) image recognition, and patient management. This narrative review article included published articles from MEDLINE/PubMed, Google Scholar and National Informatics Center egov mobile apps. The database was searched for "Artificial intelligence" and "COVID-19" and "respiratory care unit" written in the English language during a period of one year 2019-2020. The relevance of AI for patients is in hands of people with digital health tools, Aarogya setu app and Smartphone technology. AI shows about 95% accuracy in detecting COVID-19-specific chest findings. Robots with AI are being used for patient assessment and drug delivery to patients to avoid the spread of infection. The pandemic outbreak has replaced the classroom method of teaching with the online execution of teaching practices and simulators. AI algorithms have been used to develop major organ tissue characterization and intelligent pain management techniques for patients. The Blue-dot AI-based algorithm helps in providing early warning signs. The AI model automatically identifies a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection sound pressure, and light level detection. There is now no looking back as AI and machine learning are to stay in the field of training, teaching, patient care, and research in the future.