MeTSK, a meta-learning plus self-supervised strategy on fMRI graphs, improves linear-probing classification of post-traumatic epilepsy, Alzheimer's disease, and Parkinson's disease compared with direct deep learning and fMRI foundation models in low-data settings.
Prediction of post traumatic epilepsy using mri-based imaging markers
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.IV 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Generalizable Representation Learning for fMRI-based Neurological Disorder Identification
MeTSK, a meta-learning plus self-supervised strategy on fMRI graphs, improves linear-probing classification of post-traumatic epilepsy, Alzheimer's disease, and Parkinson's disease compared with direct deep learning and fMRI foundation models in low-data settings.