Long Short-Term Memory Approach for Coronavirus Disease Prediction

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Obaid Omar Ibrahim; Mohammed Mazin Abed; Mostafa Salama A.

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Journal: Journal of Information Technology Management Year:2020 | Volume:12 | Issue:supplement 2 Page(s): 11-21

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Title

Long Short-Term Memory Approach for Coronavirus Disease Prediction

Author(s)

Obaid Omar Ibrahim | Mohammed Mazin Abed | Mostafa Salama A. | Issue Writer Certificate

Keywords

Deep learning

LSTM

Prediction

COVID-19

Recurrent Neural Network (RNN)

Abstract

Corona Virus (COVID-19) is a major problem among people, and it causes suffering worldwide. Yet, the traditional Prediction models are not yet suitably efficient in catching the fundamental expertise as they cannot visualize the difficulty in the health's representation problem areas. This paper states Prediction mechanism that uses a model of Deep learning called Long Short-Term Memory (LSTM). We have carried this model out on corona virus dataset that obtained from the records of infections, deaths, and recovery cases across the world. Furthermore, producing a dataset which includes features of geographic regions (temperature and humidity) that have experienced severe virus outbreaks, risk factors, spatio-temporal analysis, and social behavior of people, a predictive model can be developed for areas where the virus is likely to spread. However, the outcomes of this study are justifiable to alert the authorities and the people to take precautions.

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APA: Copy

Obaid, Omar Ibrahim, Mohammed, Mazin Abed, & Mostafa, Salama A.. (2020). Long Short-Term Memory Approach for Coronavirus Disease Prediction. JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT, 12(supplement 2), 11-21. SID. https://sid.ir/paper/664685/en

Vancouver: Copy

Obaid Omar Ibrahim, Mohammed Mazin Abed, Mostafa Salama A.. Long Short-Term Memory Approach for Coronavirus Disease Prediction. JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT[Internet]. 2020;12(supplement 2):11-21. Available from: https://sid.ir/paper/664685/en

IEEE: Copy

Omar Ibrahim Obaid, Mazin Abed Mohammed, and Salama A. Mostafa, “Long Short-Term Memory Approach for Coronavirus Disease Prediction,” JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT, vol. 12, no. supplement 2, pp. 11–21, 2020, [Online]. Available: https://sid.ir/paper/664685/en

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