The efficacy of deep learning based LSTM model in forecasting the outbreak of contagious diseases.

COVID-19 LSTM Prediction RMSE Recurrent neural networks (RNN)

Journal

Infectious Disease Modelling
ISSN: 2468-0427
Titre abrégé: Infect Dis Model
Pays: China
ID NLM: 101692406

Informations de publication

Date de publication:
Mar 2022
Historique:
received: 21 10 2021
revised: 04 12 2021
accepted: 20 12 2021
pubmed: 4 1 2022
medline: 4 1 2022
entrez: 3 1 2022
Statut: ppublish

Résumé

The coronavirus disease that outbreak in 2019 has caused various health issues. According to the WHO, the first positive case was detected in Bangladesh on 7

Identifiants

pubmed: 34977438
doi: 10.1016/j.idm.2021.12.005
pii: S2468-0427(21)00086-5
pmc: PMC8712463
doi:

Types de publication

Journal Article

Langues

eng

Pagination

170-183

Informations de copyright

© 2021 The Authors.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Nurul Absar (N)

Department of Computer Science and Engineering, BGC Trust University, Bangladesh, Chittagong, 4381, Bangladesh.

Nazim Uddin (N)

Department of Computer Science and Engineering, BGC Trust University, Bangladesh, Chittagong, 4381, Bangladesh.

Mayeen Uddin Khandaker (MU)

Centre for Applied Physics and Radiation Technologies, School of Engineering and Technology, Sunway University, Bandar Sunway, 47500, Selangor, Malaysia.
Department of Physics, Faculty of Science and Technology, American International University-Bangladesh (AIUB), Dhaka, 1229, Bangladesh.

Habib Ullah (H)

Department of Physics, Faculty of Science and Technology, American International University-Bangladesh (AIUB), Dhaka, 1229, Bangladesh.

Classifications MeSH