RE-CONFIRM shows that standard fine-tuning of foundation models fails to recover known regional hubs in neurological disorders, while Hub-LoRA recovers them and outperforms custom models.
Convolutional neural network with sparse strategies to classify dynamic functional connectivity
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Foundation models for discovering robust biomarkers of neurological disorders from dynamic functional connectivity
RE-CONFIRM shows that standard fine-tuning of foundation models fails to recover known regional hubs in neurological disorders, while Hub-LoRA recovers them and outperforms custom models.