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Found 5 papers, 1 papers with code
Compressed representation of brain genetic transcription
The architecture of the brain is too complex to be intuitively surveyable without the use of compressed representations that project its variation into a compact, navigable space.
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.
The minimal computational substrate of fluid intelligence
The quantification of cognitive powers rests on identifying a behavioural task that depends on them.
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.
Deep forecasting of translational impact in medical research
We show that citations are only moderately predictive of translational impact as judged by inclusion in patents, guidelines, or policy documents.
