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Machine learning tackles waste management and health risks in Ghana

A new study explores the use of machine learning to address solid waste management issues in Ghana. Researchers developed a Random Forest classifier to predict illness categories based on waste disposal practices and demographic data, achieving a macro F1 score of 0.63. Additionally, a MobileNetV2 model was trained for automated waste sorting using visual recognition, reaching 88.2% accuracy and a macro F1 score of 0.87. These findings highlight the potential of AI in resource-constrained settings for both health risk prediction and waste management, while also emphasizing the need for institutional support for effective implementation. AI

IMPACT Demonstrates potential for AI in resource-constrained environments for public health and waste management.

RANK_REASON The cluster describes an academic paper detailing novel applications of machine learning models for waste management and health risk prediction.

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Machine learning tackles waste management and health risks in Ghana

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The cluster describes an academic paper detailing novel applications of machine learning models for waste management and health risk prediction.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Hilda Adwubi Osei, Catherine Tenewaa Osei, Desdemona Yaa Asobayire ·

    Learning from waste: Machine Learning for health risk prediction and computer vision-based sorting in Ghana

    arXiv:2608.25759v1 Announce Type: new Abstract: The inappropriate disposal of solid waste remains a significant public health and environmental concern worldwide, including in Ghana. Poor sanitation and improper waste management practices contribute to substantial economic costs …

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Learning from waste: Machine Learning for health risk prediction and computer vision-based sorting in Ghana

    The inappropriate disposal of solid waste remains a significant public health and environmental concern worldwide, including in Ghana. Poor sanitation and improper waste management practices contribute to substantial economic costs and avoidable deaths annually. In 2022, a field …