66 citations · 66 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 66 cited
Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research
Fabian Eitel, Marc-André Schulz, Moritz Seiler +2
By promising more accurate diagnostics and individual treatment recommendations, deep neural networks and in particular convolutional neural networks have advanced to a powerful to…
q-bio.QM2017
Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging
Dmitry Petrov, Boris A. Gutman, Shih-Hua +72
As very large studies of complex neuroimaging phenotypes become more common, human quality assessment of MRI-derived data remains one of the last major bottlenecks. Few attempts ha…