Heung-Il Suk

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Dinggang ShenProf. and Founding Dean, School of BME, ShanghaiTech University; Co-CEO, United Imaging IntelligenceVerified email at shanghaitech.edu.cn
Xiaofeng ZHUUniversity of Electronic Science and Technology of China (电子科技大学)Verified email at massey.ac.nz
Li WangAssociate Professor, Director of Developing Brain Computing Lab, UNC-Chapel HillVerified email at med.unc.edu
Yinghuan Shi（史颖欢）Nanjing UniversityVerified email at nju.edu.cn
Mingxia LiuUniversity of North Carolina at Chapel HillVerified email at med.unc.edu
Seul-Ki YeomTechnische Universität Berlin - Machine Learning GroupVerified email at tu-berlin.de
Shuiwang Ji, Professor and Truchard...Department of Computer Science & Engineering, Texas A&M UniversityVerified email at tamu.edu
Rongjian LiBank of AmericaVerified email at odu.edu
Daoqiang ZhangNanjing University of Aeronautics and AstronauticsVerified email at nuaa.edu.cn
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
Siamac FazliNazarbayev UniversityVerified email at nu.edu.kz
Kim Han ThungUniversity of North Carolina at Chapel HillVerified email at email.unc.edu
Feng LiuAssociate Professor, Tianjin Medical University General HospitalVerified email at tmu.edu.cn
Hee-Deok YangProfessor, Dept. of Computer Engineering, Chosun UniversityVerified email at chosun.ac.kr
Christian WallravenKorea UniversityVerified email at korea.ac.kr
Seong-Whan LeeProfessor of Artificial Intelligence and Brain Engineering, Korea UniversityVerified email at korea.ac.kr
Chong-Yaw Wee

Heung-Il Suk

Professor, Department of Artificial Intelligence, Korea University

Verified email at korea.ac.kr - Homepage

Machine/Deep Learning Medical Image Analysis AI for Healthcare Brain-Computer Interface


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Deep learning in medical image analysis D Shen, G Wu, HI Suk Annual review of biomedical engineering 19 (1), 221-248, 2017	5217	2017
Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis HI Suk, SW Lee, D Shen, Alzheimer's Disease Neuroimaging Initiative NeuroImage 101, 569-582, 2014	1034	2014
Deep learning based imaging data completion for improved brain disease diagnosis R Li, W Zhang, HI Suk, L Wang, J Li, D Shen, S Ji Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014	618	2014
Latent feature representation with stacked auto-encoder for AD/MCI diagnosis HI Suk, SW Lee, D Shen, Alzheimer’s Disease Neuroimaging Initiative Brain Structure and Function 220, 841-859, 2015	611	2015
Deep learning-based feature representation for AD/MCI classification HI Suk, D Shen Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013	585	2013
State-space model with deep learning for functional dynamics estimation in resting-state fMRI HI Suk, CY Wee, SW Lee, D Shen NeuroImage 129, 292-307, 2016	353	2016
Deep ensemble learning of sparse regression models for brain disease diagnosis HI Suk, SW Lee, D Shen, Alzheimer’s Disease Neuroimaging Initiative Medical image analysis 37, 101-113, 2017	328	2017
A novel Bayesian framework for discriminative feature extraction in brain-computer interfaces HI Suk, SW Lee IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (2), 286-299, 2012	265	2012
Hand gesture recognition based on dynamic Bayesian network framework HI Suk, BK Sin, SW Lee Pattern recognition 43 (9), 3059-3072, 2010	253	2010
A novel relational regularization feature selection method for joint regression and classification in AD diagnosis X Zhu, HI Suk, L Wang, SW Lee, D Shen, ... Medical image analysis 38, 205-214, 2017	249	2017
A novel matrix-similarity based loss function for joint regression and classification in AD diagnosis X Zhu, HI Suk, D Shen NeuroImage 100, 91-105, 2014	234	2014
Subspace regularized sparse multitask learning for multiclass neurodegenerative disease identification X Zhu, HI Suk, SW Lee, D Shen IEEE Transactions on Biomedical Engineering 63 (3), 607-618, 2015	229	2015
Deep sparse multi-task learning for feature selection in Alzheimer’s disease diagnosis HI Suk, SW Lee, D Shen, Alzheimer’s Disease Neuroimaging Initiative Brain Structure and Function 221, 2569-2587, 2016	178	2016
Commanding a brain-controlled wheelchair using steady-state somatosensory evoked potentials KT Kim, HI Suk, SW Lee IEEE Transactions on Neural Systems and Rehabilitation Engineering 26 (3 …, 2016	164	2016
Person authentication from neural activity of face-specific visual self-representation SK Yeom, HI Suk, SW Lee Pattern recognition 46 (4), 1159-1169, 2013	146	2013
Multimodal manifold-regularized transfer learning for MCI conversion prediction B Cheng, M Liu, HI Suk, D Shen, D Zhang Brain imaging and behavior 9 (4), 913-926, 2015	115	2015
Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings Y Shi, HI Suk, M Liu Springer, 2018	113	2018
Non-homogeneous spatial filter optimization for ElectroEncephaloGram (EEG)-based motor imagery classification TE Kam, HI Suk, SW Lee Neurocomputing 108, 58-68, 2013	112	2013
An introduction to neural networks and deep learning HI Suk Deep Learning for Medical Image Analysis, 3-24, 2017	105	2017
Canonical feature selection for joint regression and multi-class identification in Alzheimer’s disease diagnosis X Zhu, HI Suk, SW Lee, D Shen Brain imaging and behavior 10, 818-828, 2016	105	2016

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