Modeling and Forecasting Tuberculosis Cases Using Machine Learning and Deep Learning Approaches: A Comparative Study-Reference-Cited by-同舟云学术

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Modeling and Forecasting Tuberculosis Cases Using Machine Learning and Deep Learning Approaches: A Comparative Study

Published:2022-09-22 Issue: Volume: Page:157-171
ISSN:2367-4512
Container-title:Data Management, Analytics and Innovation
language:
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Author:

Abdualgalil Bilal^ORCID,Abraham Sajimon^ORCID,Ismael Waleed M.^ORCID,George Dais^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-2600-6_11

Reference22 articles.

1. R. Miggiano, M. Rizzi, D.M. Ferraris, Mycobacterium tuberculosis pathogenesis, infection prevention and treatment. Pathogens 9(5) (2020)

2. I.D. Page, R. Byanyima, S. Hosmane, N. Onyachi, C. Opira, M. Richardson, R. Sawyer, A. Sharman, D.W. Denning, Chronic pulmonary aspergillosis commonly complicates treated pulmonary tuberculosis with residual cavitation. Eur. Respir. J. 53(3) (2019)

3. W.H.O. (WHO), Tuberculosis. http://www.who.int/news-room/fact-sheets/detail/tuberculosis. Last accessed 30 May 2021

4. H. Mohajan, Tuberculosis is a Fatal Disease Among Some Developing Countries of the World (2014)

5. W.H.O. (WHO), Tuberculosis. http://www.who.int/news-room/fact-sheets/detail/tuberculosis. Last accessed 25 June 2021

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1. Deep learning-based method for sentiment analysis for patients’ drug reviews;PeerJ Computer Science;2024-04-29

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