output
20082026
most citedNiftyNet: a deep-learning platform for medical imaging

563 citations

Showing 2023Show all

6 papers · 1 filter

stat.ML2023★ 5 cited

Bayesian sparsification for deep neural networks with Bayesian model reduction

Dimitrije Marković, Karl J. Friston, Stefan J. Kiebel

Deep learning's immense capabilities are often constrained by the complexity of its models, leading to an increasing demand for effective sparsification techniques. Bayesian sparsi…

cs.LG2023★ 1 cited

Compressed representation of brain genetic transcription

James K Ruffle, Henry Watkins, Robert J Gray +3

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.…

q-bio.NC2023★ 7 cited

Computational limits to the legibility of the imaged human brain

James K Ruffle, Robert J Gray, Samia Mohinta +5

Our knowledge of the organisation of the human brain at the population-level is yet to translate into power to predict functional differences at the individual-level, limiting clin…

q-bio.NC2023★ 15 cited

Linking fast and slow: the case for generative models

Johan Medrano, Karl J. Friston, Peter Zeidman

A pervasive challenge in neuroscience is testing whether neuronal connectivity changes over time due to specific causes, such as stimuli, events, or clinical interventions. Recent…

q-bio.QM2023★ 1 cited

Individualized prescriptive inference in ischaemic stroke

Dominic Giles, Chris Foulon, Guilherme Pombo +8

The gold standard in the treatment of ischaemic stroke is set by evidence from randomized controlled trials, based on simple descriptions of presumptively homogeneous populations.…

q-bio.GN2023★ 17 cited

Brain tumour genetic network signatures of survival

James K Ruffle, Samia Mohinta, Guilherme Pombo +6

Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology. Gliomas are characterised by distinct combinations of genetic and…