RESUMEN
COVID-19, more popularly known as novel corona virus, is associated with the respiratory disorder in humans which has been declared as a global epidemic and pandemic in the first quarter of the year 2020 by the world health organization. During the COVID-19 pandemic, young people's education and social networks were severely disrupted. The inquiry on the experiences of the victims will help the health sector to change the strategies of care during such public health emergency. The lockdown and subsequent school closures established a new life routine for adolescents, centred on spending time with family and temporarily interrupting face-to-face peer relationships. In this regard, similar to others, significant autobiographical events. To explore the lived in experiences of the COVID-19 victims. Qualitative approach, with phenomenological research design, was used among 15 COVID 19 victims selected using a non probability convenient sampling technique. A one - one indepth interview was conducted using a semi structured questionnaire with 7 themes. Participants who were affected with severe symptoms for 2-3 days had variant psychological experiences like fear of spread, guilt, scared, anxious. Presence of respiratory and psychological symptoms decreased the sleep. Role change had been identified in the family support. Economic needs were manageable with their savings and monthly salary. Practicing spiritual values were the background for the recovery of the victims. The study has brought the perception of approaching the disease with positive attitude for speedy recovery.Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
RESUMEN
Everybody, around the globe, is aware that their kids, relatives, and family are suffering from the pandemic COVID-19. S everal people are still facing post-COVID-19 issues. During COVID-19's second wave, mucormycosis, sometimes known as "black fungus, " plagued people, especially those who had previously been infected with the virus. The clinical manifestations of mucormycosis are quite varied, the disease affects the skin, subcutaneous fatty tissue, and visceral organs such as the eyes and brain. This paper surveys the Mucormycosis-affected eye diseases due to post-COVID-19 complications and leverages the Machine learning model to differentiate it from other eye diseases. COVID-19-associated Mucormycosis carries a very high mortality rate and timely detection that can assist people in starting therapy at an early stage of the disease, increasing their chances of recovery. Though it was evaluated for a specific disease (COVID-19-associated mucormycosis) we ended up developing a framework that can detect other eye diseases. Thus, the goal of this research is to distinguish Mucormycosis from other eye diseases such as Bulging Eyes, Cataracts, Crossed Eyes, Glaucoma, and Uveitis. This study implies Deep learning techniques with a Convolutional Neural Network based on the TensorFlow and Keras model to detect and make use of computer vision to accurately classify eye diseases. We achieved a precision of 70% in this study by developing a webpage using the trained model for an eye diseases evaluation. © 2022 IEEE