Development of Information Security Management Assessment Model for the Financial Sector. - Eun Oh; Tae-Sung Kim; Tae-Hee Cho (WISA, 2016)

Better Diffusion Segmentation in Acute Ischemic Stroke Through Automatic Tree Learning Anomaly Segmentation. - Jens K. Boldsen; Thorbjørn S. Engedal; Salvador Pedraza; Tae-Hee Cho; Götz Thomalla; Norbert Nighoghossian; Jean-Claude Baron; Jens Fiehler; Leif Østergaard; Kim Mouridsen (Frontiers Neuroinformatics, 2018)

Local spatio-temporal encoding of raw perfusion MRI for the prediction of final lesion in stroke. - Mathilde Giacalone; Pejman Rasti; Noëlie Debs; Carole Frindel; Tae-Hee Cho; Emmanuel Grenier; David Rousseau (Medical Image Anal., 2018)

Evaluation of the Realism of an MRI Simulator for Stroke Lesion Prediction Using Convolutional Neural Network. - Noëlie Debs; Méghane Decroocq; Tae-Hee Cho; David Rousseau; Carole Frindel (SASHIMI@MICCAI, 2019)

Simulated perfusion MRI data to boost training of convolutional neural networks for lesion fate prediction in acute stroke. - Noëlie Debs; Pejman Rasti; Léon Victor; Tae-Hee Cho; Carole Frindel; David Rousseau (Comput. Biol. Medicine, 2020)

CNN-LSTM Based Multimodal MRI and Clinical Data Fusion for Predicting Functional Outcome in Stroke Patients. - Nima Hatami; Tae-Hee Cho; Laura Mechtouff; Omer Faruk Eker; David Rousseau; Carole Frindel (EMBC, 2022)

A Novel Autoencoders-LSTM Model for Stroke Outcome Prediction Using Multimodal MRI Data. - Nima Hatami; Laura Mechtouff; David Rousseau; Tae-Hee Cho; Omer Faruk Eker; Yves Berthezene; Carole Frindel (ISBI, 2023)

Difficulty Metrics Study for Curriculum-Based Deep Learning in the Context of Stroke Lesion Segmentation. - Juliette Moreau; Laura Mechtouff; David Rousseau; Tae-Hee Cho; Omer Faruk Eker; Yves Berthezene; Carole Frindel (ISBI, 2023)

Fusion of Dwi Image and Clinical Variables for Stroke Outcome Prediction Using Tabular Transformer. - Mingtian Liu; Nima Hatami; Laura Mechtouff; Tae-Hee Cho; Carole Lartizien; Carole Frindel (ISBI, 2025)