M2LG-DG: A Multi-modal Local-Global Domain Generalization Framework for Cross-site Major Depressive Disorder Classification

Not provided in the abstract

multimodaldomain generalizationneuroimagingclassification

2609.09186

Builder Relevance

70%

1h ago

Abstract

This paper presents a framework for improving cross-site classification of major depressive disorder using multimodal data.

Reality Card

Core Claim

M2LG-DG achieves an AUC of 69.48% for cross-site major depressive disorder classification, outperforming the closest comparison method by 2.18 percentage points.

Method / Result

Achieved an AUC of 69.48% on four held-out REST-meta-MDD sites.

Limitations

The paper does not specify the authors or provide details on the reproducibility of the results.

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