ABSTRACT
Artificial intelligence (AI) and machine learning (ML) have become essentials part of our lives by having their applications in various fields. Artificial intelligence is a technology that allows a machine to behave like a human. Machine learning is a subdivision of artificial intelligence that helps a machine to automatically learn from past data with more accurate predicting outcomes. In today's life, especially during the COVID-19 pandemic, our lives run online and almost all work is done online like office work, education, shopping, medical facilities, etc., as are so many cases where machine learning is used in the finance sector like financial monitoring, making investment predictions, process automation, secure transactions, risk management, financial advisory, customer data management, decision making, business analysis, and customer service-level improvement. © 2023, IGI Global. All rights reserved.
ABSTRACT
As a major virus outbreak in the 21st century, the Coronavirus disease 2019 (COVID-19) pandemic has led to unprecedented hazards to mental health globally. While psychological support is being provided to patients and healthcare workers, the general public's mental health requires significant attention as well. This systematic review aims to synthesize extant literature that reports on the effects of COVID-19 on psychological outcomes of the general population and its associated risk factors. A systematic search was conducted on PubMed, Embase, Medline, Web of Science, and Scopus from inception following the PRISMA guidelines. Relatively high rates of symptoms of anxiety, depression, post-traumatic stress disorder, psychological distress, and stress are reported in the general population during the COVID-19 pandemic . Risk factors associated with distress measures include female gender, younger age group, presence of chronic/psychiatric illnesses, unemployment, student status, and frequent exposure to social media/news concerning COVID-19.The COVID-19 pandemic is associated with highly significant levels of psychological distress that, in many cases, would meet the threshold for clinical relevance. Mitigating the hazardous effects of COVID-19 on mental health is an international public health priority.
ABSTRACT
Background: The COVID-19 pandemic has inflated the risks faced by healthcare workersand may increase their susceptibility to sleep and psychological problems. This cross-sectional observational study assessed the sleep and psychological problems due to the COVID-19 pandemic among healthcare workers of Employees State Insurance Corporation, an organized sector under the Ministry of Labour and Employment, India. Method: Logistic regression was used to evaluate factors associated with symptoms of anxiety, depression, insomnia and perceived stress among 492 healthcare workers in Employees State Insurance Corporation hospitals and dispensaries in Delhi and the National Capital Territory Region, India. Results: Logistic regression determined that factors of workplace type and frequency of hand washing were associated with anxiety;workplace type, job profile, occupation, formal COVID-19 training and adequate personal protective equipment were predictors of perceived stress;job profile was a common predictor of depression and insomnia;workplace type and formal COVID-19 training were associated with depression and insomnia, respectively. Limitations: This study was limited to healthcare workers in Employees State Insurance Corporation of Delhi and NCR which limits its generalizability to other regions of India. Conclusions: Healthcare workers are exposed to increased risk in the execution of their duties and require support to secure their wellbeing. Policies, systems for early detection of sleep and psychological problems, training, preparedness and efficacy in crisis management are suggested to reduce and prevent the occurrence of these problems among HCWs.
ABSTRACT
The current outbreak of the COVID-19 threatens public health worldwide, and WHO declares this as a global pandemic. Effective oral drug therapy against coronavirus did not discover yet. In order to find out an effective drug, we docked 23 compounds within the active site of 6LU7 protein of coronavirus. Among all, some antivirals exhibited very promising results against coronavirus and may be considered as a potential drug for treating COVID-19 disease. Molecular docking study revealed that isovitexin and apigenin found from nishinda (Vitex sp.) as well as our newly prepared compound (E)-4-((3,5-dibromo-2-hydroxybenzylidene)amino)-N-(5-methylisoxazol-3-yl)benzenesulfonamide showed exce-llent activity as compared to danoprevir, lopinavir, remdesivir and ritonavir. Isovitexin showed a binding affinity of -8.00 kcal/mol, whereas the binding affinity of sulfonamide compound with the coronavirus protein was -7.30 kcal/mol, which was relatively high compared to other antiviral drugs. Besides, the synthesized sulfonamide compound's absorption, distribution, metabolism, excretion, and toxicity profiles were also carried out. The compound showed excellent drug-like properties and percentage of human oral absorption. Moreover, it was found to be safe for the human body in toxicological risk assessment. [ FROM AUTHOR] Copyright of Journal of Scientific Research is the property of Rajshahi University, Faculty of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)