TY - JOUR
AU - Jamshidi, Mohammad Behdad
AU - Lalbakhsh, Ali
AU - Talla, Jakub
AU - Peroutka, Zdenek
AU - Hadjilooei, Farimah
AU - Lalbakhsh, Pedram
AU - Jamshidi, Morteza
AU - Spada, Luigi La
AU - Mirmozafari, Mirhamed
AU - Dehghani, Mojgan
AU - Sabet, Asal
AU - Roshani, Saeed
AU - Roshani, Sobhan
AU - Bayat-Makou, Nima
AU - Mohamadzade, Bahare
AU - Malek, Zahra
AU - Jamshidi, Alireza
AU - Kiani, Sarah
AU - Hashemi-Dezaki, Hamed
AU - Mohyuddin, Wahab
PY - 2020
DA - June
TI - Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment
JO - IEEE Access
EP - 109595
VL - 8
DO - https://doi.org/10.1109/access.2020.3001973
AB - COVID-19 outbreak has put the whole world in an unprecedented difficult 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 Artificial 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 Artificial 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.
PB - IEEE
UR - http://researchrepository.napier.ac.uk/Output/2677593
KW - Coronavirus (COVID-19)
KW - Digital health and technology
ER