Forecasting tuberculosis incidence: a review of time series and machine learning models for prediction and eradication strategies-Reference-Cited by-同舟云学术

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Forecasting tuberculosis incidence: a review of time series and machine learning models for prediction and eradication strategies

Published:2024-06-25 Issue: Volume: Page:1-16
ISSN:0960-3123
Container-title:International Journal of Environmental Health Research
language:en
Short-container-title:International Journal of Environmental Health Research

Author:

Maipan-Uku Jamilu Yahaya¹²³^ORCID,Cavus Nadire²³^ORCID

Affiliation:

1. Department of Computer Science, Ibrahim Badamasi Babangida University, Lapai, Nigeria

2. Department of Computer Information Systems, Near East University, Nicosia, Turkey

3. Computer Information Systems Research and Technology Centre, Near East University, Nicosia, Turkey

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/09603123.2024.2368137

Reference48 articles.

1. Prediction of Multidrug-Resistant Tuberculosis Using Machine Learning Algorithms in SWAT, Pakistan

2. Estimating the incidence of tuberculosis cases reported at a tertiary hospital in Ghana: a time series model approach

3. A machine learning-based framework for Predicting Treatment Failure in tuberculosis: A case study of six countries

4. Seasonality and Trend Forecasting of Tuberculosis Prevalence Data in Eastern Cape, South Africa, Using a Hybrid Model

5. Bonaccorso G. 2017. Machine learning algorithms. Packt Publishing Ltd. https://balasahebtarle.files.wordpress.com/2020/01/machine-learning-algorithms_text-book.pdf.

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