AI And COVID-19 Deep Learning Approaches For Diagnosis and Treatment

DOI

No DOI

Published In

Volume 3, Issue 4 (2022)

Published Online

July-August 2022

Pages

83-90

Article Type

Research Article

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Abstract: COVID-19's spread triggered an unparalleled global disaster, impacting millions of people and killing tens of thousands. COVID-19 has spread to 212 nations and territories by May 22, 2020, with a total of 5,212,172 cases and 334,915 fatalities. The use of artificial intelligence to combat infection is proposed in this research (AI). GANs, ELMs, and LSTMs are just a handful of the various Deep Learning (DL) algorithms that have been proved to function for this purpose. It offers a comprehensive bioinformatics technique that brings together structured and unstructured data sources to develop user-friendly platforms for doctors and researchers. The main purpose of these AI-based solutions is to speed up the diagnosis and treatment of COVID-19 disorders. The goal of recent publications and clinical investigations on the topic is to determine the network's inputs and goals in order to build a reliable artificial neural network-based solution to COVID-19-related difficulties. Furthermore, each platform has its own set of inputs, which contain a variety of information: B. Clinical data and medical imaging may aid in the improvement of new pathways' performance in order to attain the greatest outcomes in real-world circumstances.