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Found 5 papers, 1 papers with code
VASARI-auto: equitable, efficient, and economical featurisation of glioma MRI
We quantified: 1) agreement across neuroradiologists and VASARI-auto; 2) calibration of performance equity; 3) an economic workforce analysis; and 4) fidelity in predicting patient survival.
Computational limits to the legibility of the imaged human brain
It remains unknown whether the difficulty arises from the absence of individuating biological patterns within the brain, or from limited power to access them with the models and compute at our disposal.
Brain tumour genetic network signatures of survival
Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology.
Brain tumour segmentation with incomplete imaging data
This is a task contemporary machine learning could facilitate, especially in neuroimaging, but its ability to deal with incomplete data common in real world clinical practice remains unknown.
HIPPOCAMPAL NEURONAL REPRESENTATIONS IN CONTINUAL LEARNING
The hippocampus has long been associated with spatial memory and goal-directed spatial navigation.
