Advancing early warning mechanisms: an augmented intelligence-driven model for predicting multidimensional vulnerability levels in Afghanistan
The complex socioeconomic landscape of conflict zones demands innovative approaches to assess and predict vulnerabilities for crafting and implementing effective policies by the United Nations (UN) institutions. This article presents a groundbreaking Augmented Intelligence-driven Prediction Model de...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2025-01-01
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| Series: | Data & Policy |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2632324924000919/type/journal_article |
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