Open AccessAI-driven deep learning method for diagnosing COVID-19 symptoms
Publication year - 2021
Publication title -
international journal for innovative engineering and management research
Language(s) - English
Resource type - Journals
ISSN - 2456-5083
DOI - 10.48047/ijiemr/v10/i11/07
Subject(s) - computer science , artificial intelligence , covid-19 , deep learning , process (computing) , machine learning , artificial neural network , adversarial system , data science , medicine , disease , infectious disease (medical specialty) , pathology , operating system
The outbreak of COVID-19 put the whole world in an unprecedentedly harsh situation,horribly disrupting life around the world and killing thousands. COVID-19 remains a real threatto the public health system as it spreads to 212 countries and territories and the number of casesof infection and deaths increases to 5,212,172 and 334,915 (as of May 22, 2020). This treatiseprovides a response to virus eradication via artificial intelligence (AI). Several deep learning(DL) methods have been described to achieve this goal, including GAN (Generative AdversarialNetwork), ELM (Extreme Learning Machine), and LSTM (Long / Short Term Memory). Itdescribes an integrated bioinformatics approach that combines various aspects of informationfrom a series of orthopedic and unstructured data sources to form a user-friendly platform forphysicians and researchers. A major advantage of these AI-powered platforms is to facilitate thediagnosis and treatment process of the COVID-19 disease. The latest relevant publications andmedical reports have been investigated to select inputs and targets for networks that will facilitatearriving at reliable artificial neural network-based tools for COVID-19-related challenges. Thereare also several specific inputs per platform, including clinical data and data in various formats,such as medical images, which can improve the performance of the introduced method for thebest response in real application.