Predictive Modeling of Global Vector-Borne Diseases: Leveraging Machine Learning for Intervention Strategies-Reference-Cited by-同舟云学术

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Predictive Modeling of Global Vector-Borne Diseases: Leveraging Machine Learning for Intervention Strategies

Published:2024-01-28 Issue: Volume:11 Page:1027-1031
ISSN:
Container-title:2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)
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Author:

Tito Mokammel Hossain¹,Arifuzzaman Md²,Rahman Md. Siddiqur³,Khan Shahzad⁴,Chohan Muhammad Shahzad⁴,Nasrin Alifa⁵

Affiliation:

1. Animanl Science and Veterinary Medicine, Bangabandhu Sheikh Mujibur Rahman Science and Technology University,Gopalganj,Bangladesh

2. Civil and Environmental Engineering, King Faisal University,Al Hafuf,Saudi Arabia

3. Bangladesh Agricultural University (BAU),Department of Medicine,Mymensingh,Bangladesh

4. King Faisal University,Department of Biomedical Sciences,Al Hafuf,Saudi Arabia

5. Combined Military Hospital (CMH),Dhaka,Bangladesh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10459226/10459347/10459646.pdf?arnumber=10459646

Reference22 articles.

1. Effectiveness of community participation in vector-borne disease control

2. Vector-borne diseases,2014

3. Vector-borne diseases and climate change: a European perspective

4. Challenges in predicting climate and environmental effects on vector-borne disease episystems in a changing world

5. A comparative study of ensemble machine learning algorithms for brucellosis disease prediction

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