Abstract
Researchers from different disciplines are striving to leverage a solution for COVID-19 with a unique commitment of scientific collaborations and with cognitive technologies, and highly flexible learning processes are required to maintain the transmission of knowledge, prototype, and code by integrating the application areas to a specific culture and cross-border cooperation. The research experts in the artificial intelligence (AI) and machine learning (ML) domain were tracked and predicted with real-time data observed throughout the world regarding the pandemic situation and timely assessment of the distributed COVID-19 patient information. The considered physiological features followed by clinical tests of patients with COVID-19 offer very simple access to subsequent data transformation, which was relevant but complicated. This paper works on in-depth exploratory data analysis (EDA) prediction analysis over the global medical database of COVID-19 will be available for benefiting future artificial predictive, analytical, and biomedical research, which includes additional COVID-19 approaches associated with pandemics.
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Laxmi Lydia, E., Moses Gummadi, J., Ranjan Pattanaik, C., Krishna Mohan, A., Jaya Suma, G., Daniel, R. (2021). Interdependence in Artificial Intelligence to Empower Worldwide COVID-19 Sensitivity. In: Bindhu, V., Tavares, J.M.R.S., Boulogeorgos, AA.A., Vuppalapati, C. (eds) International Conference on Communication, Computing and Electronics Systems. Lecture Notes in Electrical Engineering, vol 733. Springer, Singapore. https://doi.org/10.1007/978-981-33-4909-4_65
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