Exploring explainable machine learning algorithms to model predictors of tobacco use among men in Sub Sahara Africa between 2018 and 2023

Exploring explainable machine learning algorithms to model predictors of tobacco use among men in Sub Sahara Africa between 2018 and 2023

Abstract Tobacco smoking is a significant public health issue in sub-Saharan Africa, with its prevalence shaped by various demographic factors. This study aimed to model predictors of tobacco use among men in Sub Sahara Africa between 2018 and 2023 using machine learning algorithms. Data from Demogr...

Full description

Saved in:
Bibliographic Details
Main Authors: Mequannent Sharew Melaku, Nebebe Demis Baykemagn, Lamrot Yohannes, Adem Tsegaw Zegeye
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Determinants
Tobacco smoking
Smokeless tobacco
Prediction
Sub-Saharan Africa
Online Access:https://doi.org/10.1038/s41598-025-09380-6
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-09380-6

Similar Items