ku-milab Goto Github PK

pl-fc

rdnn

Implementation of "Toward an Interpretable Alzheimer's Disease Diagnostic Model with Regional Abnormality Representation via Deep Learning"

rl_bci

Implementation of "A Novel RL-assisted Deep Learninng Framework for Task-informative Signals Selection and Classification for Spontaneous BCIs"

roiwisehmm

Implementation of "Modeling Regional Dynamics in Low-Frequency Fluctuation and Its Application to Autism Spectrum Disorder Diagnosis"

rstnn

Implementation of "Deep recurrent spatio-temporal neural network for motor imagery based BCI"

sfcnr

sgdal

sicr_bci

Pytorch implementation of "Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCI"

transsleep

A source code for deep learning-based autonomous sleep staging.

uhf-guided_segmentation

PyTorch implementation of "Transferring Ultra-high Field Representations for Intensity-Guided Brain Segmentation of Low Field MRI"

v-rin

Implementation of "Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series"

vrnn_gru-u

Implementation of "Uncertainty-Gated Stochastic Sequential Model for EHR Mortality Prediction"

xadlime

We propose a novel deep-learning approach through eXplainable AD Likelihood Map Estimation (XADLiME) for AD progression modeling over 3D sMRIs using clinically-guided prototype learning