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July 24, 2026BMC Public Health0 citationsOpen Access

Comparative Machine Learning Approach for Predicting Health, Economy, and Environmental Indicators

Predicting health, economy, and environmental indicators: a comparative machine learning approach

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Authors

MTMurat TekbaşEAElif Aktepe

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Overview

Randomized trial reveals predictive associations among economic growth, health indicators, and environmental sustainability.

Key Points

  • This study aims to examine the relationships among economic growth, health indicators, and environmental sustainability using machine learning methods.
  • Analyzed a large-scale panel dataset covering 217 countries from 1960–2024.
  • Implemented advanced machine learning algorithms including Random Forest and Extra Trees, and proposed a hybrid ensemble model.
  • Utilized Shapley Additive Explanations for model interpretability and variable importance analysis.
  • The hybrid ensemble model outperformed individual algorithms in prediction accuracy.
  • Health expenditures, economic growth, and innovation indicators showed high predictive importance.
  • Predictive associations were highlighted between environmental indicators, healthcare spending, and sustainable development outcomes.

Cite This Study

Tekbaş et al. (2026) studied this question.

synapsesocial.com/papers/6a63011f395161722cd15cb0https://doi.org/10.1186/s12889-026-28472-0
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