most citedMedical Transformer: Universal Brain Encoder for 3D MRI Analysis

32 citations · 36 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2021★ 32 cited

Medical Transformer: Universal Brain Encoder for 3D MRI Analysis

Eunji Jun, Seungwoo Jeong, Da-Woon Heo +1

Transfer learning has gained attention in medical image analysis due to limited annotated 3D medical datasets for training data-driven deep learning models in the real world. Exist…

cs.LG2021★ 4 cited

Multi-view Integration Learning for Irregularly-sampled Clinical Time Series

Yurim Lee, Eunji Jun, Heung-Il Suk

Electronic health record (EHR) data is sparse and irregular as it is recorded at irregular time intervals, and different clinical variables are measured at each observation point.…

cs.CV2020

Deep Recurrent Model for Individualized Prediction of Alzheimer's Disease Progression

Wonsik Jung, Eunji Jun, Heung-Il Suk

Alzheimer's disease (AD) is known as one of the major causes of dementia and is characterized by slow progression over several years, with no treatments or available medicines. In…

cs.LG2020

Uncertainty-Gated Stochastic Sequential Model for EHR Mortality Prediction

Eunji Jun, Ahmad Wisnu Mulyadi, Jaehun Choi +1

Electronic health records (EHR) are characterized as non-stationary, heterogeneous, noisy, and sparse data; therefore, it is challenging to learn the regularities or patterns inher…

cs.LG2020

Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series

Ahmad Wisnu Mulyadi, Eunji Jun, Heung-Il Suk

Electronic health records (EHR) consist of longitudinal clinical observations portrayed with sparsity, irregularity, and high-dimensionality, which become major obstacles in drawin…