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Found 6 papers, 3 papers with code
Predicting breast cancer with AI for individual risk-adjusted MRI screening and early detection
Reevaluating these regions in 10% of all cases with higher AI-predicted risk could have resulted in up to 33% early detections by a radiologist.
Segmentation of MRI head anatomy using deep volumetric networks and multiple spatial priors
The benefit of adding a TPM is generic in that it can boost the performance of established segmentation networks such as the DeepMedic and a UNet.
Multi-set Canonical Correlation Analysis simply explained
The methods differ on the criterion they optimize and the constraints placed on the solutions.
Correlated Components Analysis - Extracting Reliable Dimensions in Multivariate Data
How does one find dimensions in multivariate data that are reliably expressed across repetitions?
Adaptive Template Matching with Shift-Invariant Semi-NMF
On these data the algorithm essentially performs spike detection and unsupervised spike clustering.
Second Order Bilinear Discriminant Analysis for single trial EEG analysis
Traditional analysis methods for single-trial classification of electro-encephalography (EEG) focus on two types of paradigms: phase locked methods, in which the amplitude of the signal is used as the feature for classification, i. e. event related potentials; and second order methods, in which the feature of interest is the power of the signal, i. e event related (de)synchronization.
