Title: Artificial intelligence and COVID-19: deep learning approaches for diagnosis and treatment
Authors: Jamshidi, Mohammad
Lalbakhsh, Ali
Talla, Jakub
Peroutka, Zdeněk
Hadjilooei, Farimah
Lalbakhsh, Pedram
Jamshidi, Morteza
La Spada, Luigi
Mirmozafari, Mirhamed
Dehghani, Mojgan
Sabet, Asal
Roshani, Saeed
Roshani, Sobhan
Bayat-Makou, Nima
Mohamadzade, Bahare
Malek, Zahra
Jamshidi, Alireza
Kiani, Sarah
Hashemi Dezaki, Hamed
Mohyuddin, Wahab
Citation: JAMSHIDI, M., LALBAKHSH, A., TALLA, J., PEROUTKA, Z., HADJILOOEI, F., LALBAKHSH, P., JAMSHIDI, M., LA SPADA, L., MIRMOZAFARI, M., DEHGHANI, M., SABET, A., ROSHANI, S., ROSHANI, S., BAYAT-MAKOU, N., MOHAMADZADE, B., MALEK, Z., JAMSHIDI, A., KIANI, S., HASHEMI DEZAKI, H., MOHYUDDIN, W. Artificial intelligence and COVID-19: deep learning approaches for diagnosis and treatment. IEEE Access, 2020, roč. 8, č. 2020, s. 109581-109595. ISSN 2169-3536.
Issue Date: 2020
Publisher: IEEE
Document type: článek
URI: 2-s2.0-85087668610
ISSN: 2169-3536
Keywords in different language: artificial intelligence;big data;bioinformatics;biomedical informatics;COVID-19;deep learning;diagnosis;machine learning;treatment
Abstract in different language: COVID-19 outbreak has put the whole world in an unprecedented difcult situation bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19's spread in 212 countries and territories and increasing numbers of infected cases and death tolls mounting to 5,212,172 and 334,915 (as of May 22 2020), it remains a real threat to the public health system. This paper renders a response to combat the virus through Articial Intelligence (AI). Some Deep Learning (DL) methods have been illustrated to reach this goal, including Generative Adversarial Networks (GANs), Extreme Learning Machine (ELM), and Long /Short Term Memory (LSTM). It delineates an integrated bioinformatics approach in which different aspects of information from a continuum of structured and unstructured data sources are put together to form the user-friendly platforms for physicians and researchers. The main advantage of these AI-based platforms is to accelerate the process of diagnosis and treatment of the COVID-19 disease. The most recent related publications and medical reports were investigated with the purpose of choosing inputs and targets of the network that could facilitate reaching a reliable Articial Neural Network-based tool for challenges associated with COVID-19. Furthermore, there are some specific inputs for each platform, including various forms of the data, such as clinical data and medical imaging which can improve the performance of the introduced approaches toward the best responses in practical applications.
Rights: © IEEE
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Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/39669

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