A machine learning computational approach for the mathematical anthrax disease system in animals

The designed scheme is not applied before to get the numerical results of the anthrax disease system in animals.

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Publication Details

Journal
PLoS ONE
Published
2025-04-01
DOI
https://doi.org/10.1371/journal.pone.0320327
Citations
5
Primary Topic
Bacillus and Francisella bacterial research
Type
article
Field-Weighted Citation Impact
4.03
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article

A machine learning computational approach for the mathematical anthrax disease system in animals

Eman Simbawa, Zulqurnain Sabir
5 citations
PLoS ONE
Bacillus and Francisella bacterial research
4.03
article

A machine learning computational approach for the mathematical anthrax disease system in animals

Eman Simbawa, Zulqurnain Sabir
article en
5 citations

Abstract

The designed scheme is not applied before to get the numerical results of the anthrax disease system in animals.

PLoS ONEVol. 20(4)
King Abdulaziz University (SA), Lebanese American University (LB)
Good health and well-being
Openalex Percentile: Top 7%
Bacillus and Francisella bacterial research
4.03
DOIOpen Access PDFOpenAlex
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A machine learning computational approach for the mathematical anthrax disease system in animals — Eman Simbawa, Zulqurnain Sabir · PLoS ONE (2025) | TGRS Research Map | TGRS