Your browser doesn't support javascript.
Intelligence Methods to Fight Covid-19 Spread
11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022 ; : 1335-1340, 2022.
Article in English | Scopus | ID: covidwho-2277993
ABSTRACT
According to the COVID-19 worldwide sickness, which has wreaked devastation, over than millions of individuals from all over the globe have been afflicted. The COVID-19 virus infected a significant number of people worldwide as a result of both the latency in detecting its existence in the female organism. A.i. (AI) and Computer Vision (ML) may assist in identifying, treatment, and assessing the severity of COVID-besides all the conventional approaches now present. In order to fully understand the role of AI and ML as a crucial tool for COVID-19 and related outbreak detection, forecasting, forecasts, contacts tracking, and therapy formulation, this study aims to offer a comprehensive review of the topic. AI revolutionises diagnostic accuracy in terms of efficiency and precision. This technology holds promise for a self-driving and visible surveillance system that can enable real - time and treat people avoiding spreading the virus to others. Digital Healthcare different applications have also been discovered. This essay investigates how AI may help fight the COVID-19 pandemic. We make an effort to provide an AI-based hospital design. Ai systems (AI) is used in the infrastructure to effectively and quickly carry out health care, assessment, and treatment. © 2022 IEEE.
Keywords

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022 Year: 2022 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022 Year: 2022 Document Type: Article