What question did this study set out to answer?

The goal is to enhance mineral prospectivity mapping for rare earth elements by using deep learning techniques.

DEEP-SEAM: an explainable semi-supervised deep learning framework for mineral prospectivity mapping

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An explainable framework predicts rare earth element prospectivity in complex areas, suggesting effective exploration strategies.

The goal is to enhance mineral prospectivity mapping for rare earth elements by using deep learning techniques.
Developed DEEP-SEAM framework integrating multiple datasets.
Utilized a semi-supervised anomaly detection model (DevNet) for learning from limited labeled data.
Applied SHAP for interpreting model predictions and identifying key influencing factors.
Top 2% of mapped areas identified as containing 86% of known REE deposits.
Main predictors include radiometric signatures and geophysical attributes, aligning with geological evidence.
The framework offers a transparent approach that improves exploration efficiency.

Luo et al. (2026) studied this question.

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