NeuroBridge integrates self-supervised MRI pretraining with hippocampal tasks and gated fusion to reach 88.17% AD vs. CN accuracy on ADNI and 82.78% on OASIS, claiming gains over single-task methods with cross-cohort generalization.
Overcoming data scarcity in biomedical imaging with a foundational multi-task model
2 Pith papers cite this work. Polarity classification is still indexing.
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Medical foundation models match a ResNet-50 but are outperformed by radiomics (AUC 0.88) on external validation for renal lesion stratification in CT.
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NeuroBridge: Bridging Multi-Task MRI Knowledge for Neurodegenerative Disease Diagnosis
NeuroBridge integrates self-supervised MRI pretraining with hippocampal tasks and gated fusion to reach 88.17% AD vs. CN accuracy on ADNI and 82.78% on OASIS, claiming gains over single-task methods with cross-cohort generalization.
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Benchmarking Foundation Models for Renal Lesion Stratification in CT
Medical foundation models match a ResNet-50 but are outperformed by radiomics (AUC 0.88) on external validation for renal lesion stratification in CT.