Scholars@Duke

• Background
• 

  Education, Training, & Certifications

  • Ph.D., Korea University (South Korea) 2014
• Publications & Artistic Works
• 

  Selected Publications

  • Books

    • Suk, H. I., M. Liu, P. Yan, and C. Lian. Preface. Vol. 11861 LNCS, 2019.
    • Shi, Y., H. I. Suk, and M. Liu. Preface. Vol. 11046 LNCS, 2018.
    • Wang, Q., Y. Shi, H. I. Suk, and K. Suzuki. Preface. Vol. 10541 LNCS, 2017.
    • Wang, L., E. Adeli, Q. Wang, Y. Shi, and H. I. Suk. Preface. Vol. 10019 LNCS, 2016.

  • Academic Articles

    • Jeon, E., W. Ko, J. S. Yoon, and H. I. Suk. “Mutual Information-Driven Subject-Invariant and Class-Relevant Deep Representation Learning in BCI.” Ieee Transactions on Neural Networks and Learning Systems 34, no. 2 (February 1, 2023): 739–49. https://doi.org/10.1109/TNNLS.2021.3100583.
       Full Text
    • Heo, S., S. S. Lee, S. Y. Kim, Y. S. Lim, H. J. Park, J. S. Yoon, H. I. Suk, Y. S. Sung, B. Park, and J. S. Lee. “Prediction of Decompensation and Death in Advanced Chronic Liver Disease Using Deep Learning Analysis of Gadoxetic Acid-Enhanced MRI.” Korean Journal of Radiology 23, no. 12 (December 1, 2022): 1269–80. https://doi.org/10.3348/kjr.2022.0494.
       Full Text
    • Kim, Woo-Sung, Da-Woon Heo, Jie Shen, Uyanga Tsogt, Soyolsaikhan Odkhuu, Jaein Lee, Eunsong Kang, Sung-Wan Kim, Heung-Il Suk, and Young-Chul Chung. “Altered functional connectivity in psychotic disorder not otherwise specified.” Psychiatry Res 317 (November 2022): 114871. https://doi.org/10.1016/j.psychres.2022.114871.
       Full Text  Link to Item
    • Ko, Wonjun, Wonsik Jung, Eunjin Jeon, and Heung-Il Suk. “A Deep Generative-Discriminative Learning for Multimodal Representation in Imaging Genetics.” Ieee Trans Med Imaging 41, no. 9 (September 2022): 2348–59. https://doi.org/10.1109/TMI.2022.3162870.
       Full Text  Link to Item
    • Mulyadi, Ahmad Wisnu, Eunji Jun, and Heung-Il Suk. “Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series.” Ieee Trans Cybern 52, no. 9 (September 2022): 9684–94. https://doi.org/10.1109/TCYB.2021.3053599.
       Full Text  Link to Item
    • Lee, Yurim, Eunji Jun, Jaehun Choi, and Heung-Il Suk. “Multi-View Integrative Attention-Based Deep Representation Learning for Irregular Clinical Time-Series Data.” Ieee J Biomed Health Inform 26, no. 8 (August 2022): 4270–80. https://doi.org/10.1109/JBHI.2022.3172549.
       Full Text  Link to Item
    • Yoon, Jee Seok, Myung-Cheol Roh, and Heung-Il Suk. “A Plug-in Method for Representation Factorization in Connectionist Models.” Ieee Trans Neural Netw Learn Syst 33, no. 8 (August 2022): 3792–3803. https://doi.org/10.1109/TNNLS.2021.3054480.
       Full Text  Link to Item
    • Park, Hyo Jung, Jee Seok Yoon, Seung Soo Lee, Heung-Il Suk, Bumwoo Park, Yu Sub Sung, Seung Baek Hong, and Hwaseong Ryu. “Deep Learning-Based Assessment of Functional Liver Capacity Using Gadoxetic Acid-Enhanced Hepatobiliary Phase MRI.” Korean J Radiol 23, no. 7 (July 2022): 720–31. https://doi.org/10.3348/kjr.2021.0892.
       Full Text  Link to Item
    • Ko, Wonjun, Eunjin Jeon, Jee Seok Yoon, and Heung-Il Suk. “Semi-supervised generative and discriminative adversarial learning for motor imagery-based brain-computer interface.” Sci Rep 12, no. 1 (March 17, 2022): 4587. https://doi.org/10.1038/s41598-022-08490-9.
       Full Text  Link to Item
    • Ko, W., E. Jeon, and H. I. Suk. “A Novel RL-Assisted Deep Learning Framework for Task-Informative Signals Selection and Classification for Spontaneous BCIs.” Ieee Transactions on Industrial Informatics 18, no. 3 (March 1, 2022): 1873–82. https://doi.org/10.1109/TII.2020.3044310.
       Full Text
    • Park, R., S. Lee, Y. Sung, J. Yoon, H. I. Suk, H. Kim, and S. Choi. “Accuracy and Efficiency of Right-Lobe Graft Weight Estimation Using Deep-Learning-Assisted CT Volumetry for Living-Donor Liver Transplantation.” Diagnostics 12, no. 3 (March 1, 2022). https://doi.org/10.3390/diagnostics12030590.
       Full Text
    • Oh, K., J. S. Yoon, and H. I. Suk. “Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model.” Ieee Transactions on Pattern Analysis and Machine Intelligence, January 1, 2022. https://doi.org/10.1109/TPAMI.2022.3197845.
       Full Text
    • Phyo, J., W. Ko, E. Jeon, and H. I. Suk. “TransSleep: Transitioning-Aware Attention-Based Deep Neural Network for Sleep Staging.” Ieee Transactions on Cybernetics, January 1, 2022. https://doi.org/10.1109/TCYB.2022.3198997.
       Full Text
    • Kwon, Ji Hye, Seung Soo Lee, Jee Seok Yoon, Heung-Il Suk, Yu Sub Sung, Ho Sung Kim, Chul-Min Lee, Kang Mo Kim, So Jung Lee, and So Yeon Kim. “Liver-to-Spleen Volume Ratio Automatically Measured on CT Predicts Decompensation in Patients with B Viral Compensated Cirrhosis.” Korean J Radiol 22, no. 12 (December 2021): 1985–95. https://doi.org/10.3348/kjr.2021.0348.
       Full Text  Link to Item
    • Kim, Dong Wook, Jiyeon Ha, Seung Soo Lee, Ji Hye Kwon, Na Young Kim, Yu Sub Sung, Jee Seok Yoon, Heung-Il Suk, Yedaun Lee, and Bo-Kyeong Kang. “Population-based and Personalized Reference Intervals for Liver and Spleen Volumes in Healthy Individuals and Those with Viral Hepatitis.” Radiology 301, no. 2 (November 2021): 339–47. https://doi.org/10.1148/radiol.2021204183.
       Full Text  Link to Item
    • Jun, Eunji, Ahmad Wisnu Mulyadi, Jaehun Choi, and Heung-Il Suk. “Uncertainty-Gated Stochastic Sequential Model for EHR Mortality Prediction.” Ieee Trans Neural Netw Learn Syst 32, no. 9 (September 2021): 4052–62. https://doi.org/10.1109/TNNLS.2020.3016670.
       Full Text  Link to Item
    • Jung, Wonsik, Eunji Jun, Heung-Il Suk, and Heung-Il Alzheimer’s Disease Neuroimaging Initiative. “Deep recurrent model for individualized prediction of Alzheimer's disease progression.” Neuroimage 237 (August 15, 2021): 118143. https://doi.org/10.1016/j.neuroimage.2021.118143.
       Full Text  Link to Item
    • Min, Byoung-Kyong, Hyun-Seok Kim, Wonjun Ko, Min-Hee Ahn, Heung-Il Suk, Dimitrios Pantazis, and Robert T. Knight. “Electrophysiological Decoding of Spatial and Color Processing in Human Prefrontal Cortex.” Neuroimage 237 (August 15, 2021): 118165. https://doi.org/10.1016/j.neuroimage.2021.118165.
       Full Text  Link to Item
    • Lee, Jiyeon, Wonjun Ko, Eunsong Kang, Heung-Il Suk, and Heung-Il and  the Alzheimer’s Disease Neuroimaging Initiative. “A unified framework for personalized regions selection and functional relation modeling for early MCI identification.” Neuroimage 236 (August 1, 2021): 118048. https://doi.org/10.1016/j.neuroimage.2021.118048.
       Full Text  Link to Item
    • Ko, W., E. Jeon, S. Jeong, J. Phyo, and H. I. Suk. “A Survey on Deep Learning-Based Short/Zero-Calibration Approaches for EEG-Based Brain–Computer Interfaces.” Frontiers in Human Neuroscience 15 (May 28, 2021). https://doi.org/10.3389/fnhum.2021.643386.
       Full Text
    • Ko, W., E. Jeon, S. Jeong, and H. I. Suk. “Multi-Scale Neural Network for EEG Representation Learning in BCI.” Ieee Computational Intelligence Magazine 16, no. 2 (May 1, 2021): 31–45. https://doi.org/10.1109/MCI.2021.3061875.
       Full Text
    • Lee, Chul-Min, Seung Soo Lee, Won-Mook Choi, Kang Mo Kim, Yu Sub Sung, Sunho Lee, So Jung Lee, Jee Seok Yoon, and Heung-Il Suk. “An index based on deep learning-measured spleen volume on CT for the assessment of high-risk varix in B-viral compensated cirrhosis.” Eur Radiol 31, no. 5 (May 2021): 3355–65. https://doi.org/10.1007/s00330-020-07430-3.
       Full Text  Link to Item
    • Jun, Eunji, Kyoung-Sae Na, Wooyoung Kang, Jiyeon Lee, Heung-Il Suk, and Byung-Joo Ham. “Identifying resting-state effective connectivity abnormalities in drug-naïve major depressive disorder diagnosis via graph convolutional networks.” Hum Brain Mapp 41, no. 17 (December 2020): 4997–5014. https://doi.org/10.1002/hbm.25175.
       Full Text  Link to Item
    • Ahn, Yura, Jee Seok Yoon, Seung Soo Lee, Heung Il Suk, Jung Hee Son, Yu Sub Sung, Yedaun Lee, Bo Kyeong Kang, and Ho Sung Kim. “Deep Learning Algorithm for Automated Segmentation and Volume Measurement of the Liver and Spleen Using Portal Venous Phase Computed Tomography Images.” Korean J Radiol 21, no. 8 (August 2020): 987–97. https://doi.org/10.3348/kjr.2020.0237.
       Full Text  Link to Item
    • Shi, Yinghuan, Heung-Il Suk, Yang Gao, Seong-Whan Lee, and Dinggang Shen. “Leveraging Coupled Interaction for Multimodal Alzheimer's Disease Diagnosis.” Ieee Trans Neural Netw Learn Syst 31, no. 1 (January 2020): 186–200. https://doi.org/10.1109/TNNLS.2019.2900077.
       Full Text  Link to Item
    • Lee, Eunho, Jun-Sik Choi, Minjeong Kim, Heung-Il Suk, and Heung-Il Alzheimer’s Disease Neuroimaging Initiative. “Toward an interpretable Alzheimer's disease diagnostic model with regional abnormality representation via deep learning.” Neuroimage 202 (November 15, 2019): 116113. https://doi.org/10.1016/j.neuroimage.2019.116113.
       Full Text  Link to Item
    • Kim, Bum-Chae, Jee Seok Yoon, Jun-Sik Choi, and Heung-Il Suk. “Multi-scale gradual integration CNN for false positive reduction in pulmonary nodule detection.” Neural Netw 115 (July 2019): 1–10. https://doi.org/10.1016/j.neunet.2019.03.003.
       Full Text  Link to Item
    • Wang, Li, Yinghuan Shi, Heung-Il Suk, Alison Noble, and Ghassan Hamarneh. “Special issue on machine learning in medical imaging.” Comput Med Imaging Graph 74 (June 2019): 10–11. https://doi.org/10.1016/j.compmedimag.2019.03.003.
       Full Text  Link to Item
    • Zhu, X., H. I. Suk, and D. Shen. “Low-rank dimensionality reduction for multi-modality neurodegenerative disease identification.” World Wide Web 22, no. 2 (March 15, 2019): 907–25. https://doi.org/10.1007/s11280-018-0645-3.
       Full Text
    • Zhu, X., H. I. Suk, and D. Shen. “Group sparse reduced rank regression for neuroimaging genetic study.” World Wide Web 22, no. 2 (March 15, 2019): 673–88. https://doi.org/10.1007/s11280-018-0637-3.
       Full Text
    • Zhu, Xiaofeng, Heung-Il Suk, Seong-Whan Lee, and Dinggang Shen. “Discriminative self-representation sparse regression for neuroimaging-based alzheimer's disease diagnosis.” Brain Imaging Behav 13, no. 1 (February 2019): 27–40. https://doi.org/10.1007/s11682-017-9731-x.
       Full Text  Link to Item
    • Jun, Eunji, Eunsong Kang, Jaehun Choi, and Heung-Il Suk. “Modeling regional dynamics in low-frequency fluctuation and its application to Autism spectrum disorder diagnosis.” Neuroimage 184 (January 1, 2019): 669–86. https://doi.org/10.1016/j.neuroimage.2018.09.043.
       Full Text  Link to Item
    • Kim, Keun-Tae, Heung-Il Suk, and Seong-Whan Lee. “Commanding a Brain-Controlled Wheelchair Using Steady-State Somatosensory Evoked Potentials.” Ieee Trans Neural Syst Rehabil Eng 26, no. 3 (March 2018): 654–65. https://doi.org/10.1109/TNSRE.2016.2597854.
       Full Text  Link to Item
    • Kam, Tae-Eui, Heung-Il Suk, and Seong-Whan Lee. “Multiple functional networks modeling for autism spectrum disorder diagnosis.” Hum Brain Mapp 38, no. 11 (November 2017): 5804–21. https://doi.org/10.1002/hbm.23769.
       Full Text  Link to Item
    • Min, B. K., H. I. Suk, M. H. Ahn, M. H. Lee, and S. W. Lee. “Individual Identification Using Cognitive Electroencephalographic Neurodynamics.” Ieee Transactions on Information Forensics and Security 12, no. 9 (September 1, 2017): 2159–67. https://doi.org/10.1109/TIFS.2017.2699944.
       Full Text
    • Shen, Dinggang, Guorong Wu, and Heung-Il Suk. “Deep Learning in Medical Image Analysis.” Annu Rev Biomed Eng 19 (June 21, 2017): 221–48. https://doi.org/10.1146/annurev-bioeng-071516-044442.
       Full Text  Link to Item
    • Zhu, Xiaofeng, Heung-Il Suk, Li Wang, Seong-Whan Lee, Dinggang Shen, and Dinggang Alzheimer’s Disease Neuroimaging Initiative. “A novel relational regularization feature selection method for joint regression and classification in AD diagnosis.” Med Image Anal 38 (May 2017): 205–14. https://doi.org/10.1016/j.media.2015.10.008.
       Full Text  Link to Item
    • Suk, Heung-Il, Seong-Whan Lee, Dinggang Shen, and Dinggang Alzheimer’s Disease Neuroimaging Initiative. “Deep ensemble learning of sparse regression models for brain disease diagnosis.” Med Image Anal 37 (April 2017): 101–13. https://doi.org/10.1016/j.media.2017.01.008.
       Full Text  Link to Item
    • Park, Ki-Hee, Heung-Il Suk, and Seong-Whan Lee. “Position-Independent Decoding of Movement Intention for Proportional Myoelectric Interfaces.” Ieee Trans Neural Syst Rehabil Eng 24, no. 9 (September 2016): 928–39. https://doi.org/10.1109/TNSRE.2015.2481461.
       Full Text  Link to Item
    • Zhu, Xiaofeng, Heung-Il Suk, Seong-Whan Lee, and Dinggang Shen. “Canonical feature selection for joint regression and multi-class identification in Alzheimer's disease diagnosis.” Brain Imaging Behav 10, no. 3 (September 2016): 818–28. https://doi.org/10.1007/s11682-015-9430-4.
       Full Text  Link to Item
    • Li, Zhou, Heung-Il Suk, Dinggang Shen, and Lexin Li. “Sparse Multi-Response Tensor Regression for Alzheimer's Disease Study With Multivariate Clinical Assessments.” Ieee Trans Med Imaging 35, no. 8 (August 2016): 1927–36. https://doi.org/10.1109/TMI.2016.2538289.
       Full Text  Link to Item
    • Suk, Heung-Il, Seong-Whan Lee, Dinggang Shen, and Dinggang Alzheimer’s Disease Neuroimaging Initiative. “Deep sparse multi-task learning for feature selection in Alzheimer's disease diagnosis.” Brain Struct Funct 221, no. 5 (June 2016): 2569–87. https://doi.org/10.1007/s00429-015-1059-y.
       Full Text  Link to Item
    • Suk, Heung-Il, Chong-Yaw Wee, Seong-Whan Lee, and Dinggang Shen. “State-space model with deep learning for functional dynamics estimation in resting-state fMRI.” Neuroimage 129 (April 1, 2016): 292–307. https://doi.org/10.1016/j.neuroimage.2016.01.005.
       Full Text  Link to Item
    • Zhu, Xiaofeng, Heung-Il Suk, Seong-Whan Lee, and Dinggang Shen. “Subspace Regularized Sparse Multitask Learning for Multiclass Neurodegenerative Disease Identification.” Ieee Trans Biomed Eng 63, no. 3 (March 2016): 607–18. https://doi.org/10.1109/TBME.2015.2466616.
       Full Text  Link to Item
    • Cheng, Bo, Mingxia Liu, Heung-Il Suk, Dinggang Shen, Daoqiang Zhang, and Daoqiang Alzheimer’s Disease Neuroimaging Initiative. “Multimodal manifold-regularized transfer learning for MCI conversion prediction.” Brain Imaging Behav 9, no. 4 (December 2015): 913–26. https://doi.org/10.1007/s11682-015-9356-x.
       Full Text  Link to Item
    • Lee, D. G., H. I. Suk, S. K. Park, and S. W. Lee. “Motion Influence Map for Unusual Human Activity Detection and Localization in Crowded Scenes.” Ieee Transactions on Circuits and Systems for Video Technology 25, no. 10 (October 1, 2015): 1612–23. https://doi.org/10.1109/TCSVT.2015.2395752.
       Full Text
    • Suk, Heung-Il, Chong-Yaw Wee, Seong-Whan Lee, and Dinggang Shen. “Supervised Discriminative Group Sparse Representation for Mild Cognitive Impairment Diagnosis.” Neuroinformatics 13, no. 3 (July 2015): 277–95. https://doi.org/10.1007/s12021-014-9241-6.
       Full Text  Link to Item
    • Cho, S. S., A. R. Lee, H. I. Suk, J. S. Park, and S. W. Lee. “Volumetric spatial feature representation for view-invariant human action recognition using a depth camera.” Optical Engineering 54, no. 3 (March 1, 2015). https://doi.org/10.1117/1.OE.54.3.033102.
       Full Text
    • Suk, Heung-Il, Seong-Whan Lee, Dinggang Shen, and Dinggang Alzheimer’s Disease Neuroimaging Initiative. “Latent feature representation with stacked auto-encoder for AD/MCI diagnosis.” Brain Struct Funct 220, no. 2 (March 2015): 841–59. https://doi.org/10.1007/s00429-013-0687-3.
       Full Text  Link to Item
    • Wang, Liye, Chong-Yaw Wee, Heung-Il Suk, Xiaoying Tang, and Dinggang Shen. “MRI-based intelligence quotient (IQ) estimation with sparse learning.” Plos One 10, no. 3 (2015): e0117295. https://doi.org/10.1371/journal.pone.0117295.
       Full Text  Link to Item
    • Suk, Heung-Il, Seong-Whan Lee, Dinggang Shen, and Dinggang Alzheimer’s Disease Neuroimaging Initiative. “Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis.” Neuroimage 101 (November 1, 2014): 569–82. https://doi.org/10.1016/j.neuroimage.2014.06.077.
       Full Text  Link to Item
    • Zhu, Xiaofeng, Heung-Il Suk, and Dinggang Shen. “A novel matrix-similarity based loss function for joint regression and classification in AD diagnosis.” Neuroimage 100 (October 15, 2014): 91–105. https://doi.org/10.1016/j.neuroimage.2014.05.078.
       Full Text  Link to Item
    • Suk, H. I., and D. Shen. “Subclass-based multi-task learning for Alzheimer's disease diagnosis.” Frontiers in Aging Neuroscience 6, no. JUN (January 1, 2014): 1–20. https://doi.org/10.3389/fnagi.2014.00168.
       Full Text
    • Suk, Heung-Il, Siamac Fazli, Jan Mehnert, Klaus-Robert Müller, and Seong-Whan Lee. “Predicting BCI subject performance using probabilistic spatio-temporal filters.” Plos One 9, no. 2 (2014): e87056. https://doi.org/10.1371/journal.pone.0087056.
       Full Text  Link to Item
    • Wang, X., L. Wang, H. I. Suk, and D. Shen. “Online discriminative multi-atlas learning for isointense infant brain segmentation.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8679 (January 1, 2014): 297–305. https://doi.org/10.1007/978-3-319-10581-9_37.
       Full Text
    • Zhu, X., H. I. Suk, and D. Shen. “Sparse discriminative feature selection for multi-class Alzheimer’s Disease classification.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8679 (January 1, 2014): 157–64. https://doi.org/10.1007/978-3-319-10581-9_20.
       Full Text
    • Zhu, Xiaofeng, Heung-Il Suk, and Dinggang Shen. “Multi-modality canonical feature selection for Alzheimer's disease diagnosis.” Med Image Comput Comput Assist Interv 17, no. Pt 2 (2014): 162–69. https://doi.org/10.1007/978-3-319-10470-6_21.
       Full Text  Link to Item
    • Kam, T. E., H. I. Suk, and S. W. Lee. “Non-homogeneous spatial filter optimization for ElectroEncephaloGram (EEG)-based motor imagery classification.” Neurocomputing 108 (May 2, 2013): 58–68. https://doi.org/10.1016/j.neucom.2012.12.002.
       Full Text
    • Yeom, S. K., H. I. Suk, and S. W. Lee. “Person authentication from neural activity of face-specific visual self-representation.” Pattern Recognition 46, no. 4 (April 1, 2013): 1159–69. https://doi.org/10.1016/j.patcog.2012.10.023.
       Full Text
    • Suk, Heung-Il, and Seong-Whan Lee. “A novel Bayesian framework for discriminative feature extraction in Brain-Computer Interfaces.” Ieee Trans Pattern Anal Mach Intell 35, no. 2 (February 2013): 286–99. https://doi.org/10.1109/TPAMI.2012.69.
       Full Text  Link to Item
    • Suk, H. I., Y. Wang, and S. W. Lee. “Incremental sparse Pseudo-input Gaussian process regression.” International Journal of Pattern Recognition and Artificial Intelligence 26, no. 8 (December 1, 2012). https://doi.org/10.1142/S021800141250019X.
       Full Text
    • Hur, D., H. I. Suk, C. Wallraven, and S. W. Lee. “Biased manifold learning for view invariant body pose estimation.” International Journal of Wavelets, Multiresolution and Information Processing 10, no. 6 (November 1, 2012). https://doi.org/10.1142/S0219691312500580.
       Full Text
    • Yang, H. D., H. I. Suk, and S. W. Lee. “Accelerating generalized iterative scaling based on staggered aitken method for on-line conditional random fields.” International Journal of Wavelets, Multiresolution and Information Processing 10, no. 6 (November 1, 2012). https://doi.org/10.1142/S0219691312500592.
       Full Text
    • Suk, H. I., A. K. Jain, and S. W. Lee. “A network of dynamic probabilistic models for human interaction analysis.” Ieee Transactions on Circuits and Systems for Video Technology 21, no. 7 (July 1, 2011): 932–45. https://doi.org/10.1109/TCSVT.2011.2133570.
       Full Text
    • Suk, H. I., and S. W. Lee. “Subject and class specific frequency bands selection for multiclass motor imagery classification.” International Journal of Imaging Systems and Technology 21, no. 2 (June 1, 2011): 123–30. https://doi.org/10.1002/ima.20283.
       Full Text
    • Suk, H. I., B. K. Sin, and S. W. Lee. “Hand gesture recognition based on dynamic Bayesian network framework.” Pattern Recognition 43, no. 9 (January 1, 2010): 3059–72. https://doi.org/10.1016/j.patcog.2010.03.016.
       Full Text

  • Book Sections

    • Suk, H. I. “An Introduction to Neural Networks and Deep Learning.” In Deep Learning for Medical Image Analysis, 3–24, 2017. https://doi.org/10.1016/B978-0-12-810408-8.00002-X.
       Full Text
    • Suk, H. I., S. W. Lee, and D. Shen. “A hybrid of deep network and hidden markov model for MCI identification with resting-state fMRI.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9349:573–80, 2015. https://doi.org/10.1007/978-3-319-24553-9_70.
       Full Text

  • Conference Papers

    • Ko, W., and H. I. Suk. “EEG-Oriented Self-Supervised Learning and Cluster-Aware Adaptation.” In International Conference on Information and Knowledge Management, Proceedings, 4143–47, 2022. https://doi.org/10.1145/3511808.3557589.
       Full Text
    • Jeong, S., W. Jung, J. Sohn, and H. I. Suk. “Deep Geometrical Learning for Alzheimer's Disease Progression Modeling.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 2022-November:211–20, 2022. https://doi.org/10.1109/ICDM54844.2022.00031.
       Full Text
    • Jeong, S., W. Ko, A. W. Mulyadi, and H. I. Suk. “Continuous Riemannian Geometric Learning for Sleep Staging Classification.” In International Winter Conference on Brain Computer Interface, Bci, Vol. 2022-February, 2022. https://doi.org/10.1109/BCI53720.2022.9734855.
       Full Text
    • Kang, E., D. W. Heo, and H. I. Suk. “Prototype Learning of Inter-network Connectivity for ASD Diagnosis and Personalized Analysis.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13433 LNCS:334–43, 2022. https://doi.org/10.1007/978-3-031-16437-8_32.
       Full Text
    • Ko, W., E. Jeon, and H. I. Suk. “Spectro-Spatio-Temporal EEG Representation Learning for Imagined Speech Recognition.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13189 LNCS:335–46, 2022. https://doi.org/10.1007/978-3-031-02444-3_25.
       Full Text
    • Lee, J., K. Oh, D. Shen, and H. I. Suk. “A Novel Knowledge Keeper Network for 7T-Free but 7T-Guided Brain Tissue Segmentation.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13435 LNCS:330–39, 2022. https://doi.org/10.1007/978-3-031-16443-9_32.
       Full Text
    • Phyo, J., W. Ko, E. Jeon, and H. Suk. “ENHANCING CONTEXTUAL ENCODING WITH STAGE-CONFUSION AND STAGE-TRANSITION ESTIMATION FOR EEG-BASED SLEEP STAGING.” In Icassp, Ieee International Conference on Acoustics, Speech and Signal Processing  Proceedings, 2022-May:1301–5, 2022. https://doi.org/10.1109/ICASSP43922.2022.9746353.
       Full Text
    • Jeong, S., E. Jeon, W. Ko, and H. I. Suk. “Fine-grained Temporal Attention Network for EEG-based Seizure Detection.” In 9th Ieee International Winter Conference on Brain Computer Interface, Bci 2021, 2021. https://doi.org/10.1109/BCI51272.2021.9385307.
       Full Text
    • Jung, W., D. W. Heo, E. Jeon, J. Lee, and H. I. Suk. “Inter-regional High-Level Relation Learning from Functional Connectivity via Self-supervision.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12902 LNCS:284–93, 2021. https://doi.org/10.1007/978-3-030-87196-3_27.
       Full Text
    • Ko, W., W. Jung, E. Jeon, A. W. Mulyadi, and H. I. Suk. “ENGINE: Enhancing Neuroimaging and Genetic Information by Neural Embedding.” In Proceedings  Ieee International Conference on Data Mining, Icdm, 2021-December:1162–67, 2021. https://doi.org/10.1109/ICDM51629.2021.00139.
       Full Text
    • Lee, J., E. Kang, E. Jeon, and H. I. Suk. “Meta-modulation Network for Domain Generalization in Multi-site fMRI Classification.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12905 LNCS:500–509, 2021. https://doi.org/10.1007/978-3-030-87240-3_48.
       Full Text
    • Ko, W., K. Oh, E. Jeon, and H. I. Suk. “VIGNet: A Deep Convolutional Neural Network for EEG-based Driver Vigilance Estimation.” In 8th International Winter Conference on Brain Computer Interface, Bci 2020, 2020. https://doi.org/10.1109/BCI48061.2020.9061668.
       Full Text
    • Jeon, E., E. Kang, J. Lee, T. E. Kam, and H. I. Suk. “Enriched Representation Learning in Resting-State fMRI for Early MCI Diagnosis.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12267 LNCS:397–406, 2020. https://doi.org/10.1007/978-3-030-59728-3_39.
       Full Text
    • Jun, E., A. W. Mulyadi, and H. I. Suk. “Stochastic Imputation and Uncertainty-Aware Attention to EHR for Mortality Prediction.” In Proceedings of the International Joint Conference on Neural Networks, Vol. 2019-July, 2019. https://doi.org/10.1109/IJCNN.2019.8852132.
       Full Text
    • Jeon, E., W. Ko, and H. I. Suk. “Domain Adaptation with Source Selection for Motor-Imagery based BCI.” In 7th International Winter Conference on Brain Computer Interface, Bci 2019, 2019. https://doi.org/10.1109/IWW-BCI.2019.8737340.
       Full Text
    • Ko, W., E. Jeon, J. Lee, and H. I. Suk. “Semi-Supervised Deep Adversarial Learning for Brain-Computer Interface.” In 7th International Winter Conference on Brain Computer Interface, Bci 2019, 2019. https://doi.org/10.1109/IWW-BCI.2019.8737345.
       Full Text
    • Jung, W., A. W. Mulyadi, and H. I. Suk. “Unified modeling of imputation, forecasting, and prediction for AD progression.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11767 LNCS:168–76, 2019. https://doi.org/10.1007/978-3-030-32251-9_19.
       Full Text
    • Ko, W., J. Yoon, E. Kang, E. Jun, J. S. Choi, and H. I. Suk. “Deep recurrent spatiooral neural network for motor imagery based BCI.” In 2018 6th International Conference on Brain Computer Interface, Bci 2018, 2018-January:1–3, 2018. https://doi.org/10.1109/IWW-BCI.2018.8311535.
       Full Text
    • Choi, J. S., E. Lee, and H. I. Suk. “Regional abnormality representation learning in structural MRI for AD/MCI diagnosis.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11046 LNCS:64–72, 2018. https://doi.org/10.1007/978-3-030-00919-9_8.
       Full Text
    • Kang, E., and H. I. Suk. “Probabilistic source separation on resting-state fMRI and its use for early MCI identification.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11072 LNCS:275–83, 2018. https://doi.org/10.1007/978-3-030-00931-1_32.
       Full Text
    • Jun, E., and H. I. Suk. “Region-wise stochastic pattern modeling for autism spectrum disorder identification and temporal dynamics analysis.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10511 LNCS:143–51, 2017. https://doi.org/10.1007/978-3-319-67159-8_17.
       Full Text
    • Kang, E. S., B. C. Kim, and H. I. Suk. “An empirical suggestion for collaborative learning in motor imagery-based BCIs.” In 4th International Winter Conference on Brain Computer Interface, Bci 2016, 2016. https://doi.org/10.1109/IWW-BCI.2016.7457450.
       Full Text
    • Kim, B. C., Y. S. Sung, and H. I. Suk. “Deep feature learning for pulmonary nodule classification in a lung CT.” In 4th International Winter Conference on Brain Computer Interface, Bci 2016, 2016. https://doi.org/10.1109/IWW-BCI.2016.7457462.
       Full Text
    • Suk, H. I., and D. Shen. “Deep ensemble sparse regression network for alzheimer’s disease diagnosis.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10019 LNCS:113–21, 2016. https://doi.org/10.1007/978-3-319-47157-0_14.
       Full Text
    • Zhu, X., H. I. Suk, H. Huang, and D. Shen. “Structured sparse low-rank regression model for brain-wide and genome-wide associations.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9900 LNCS:344–52, 2016. https://doi.org/10.1007/978-3-319-46720-7_40.
       Full Text
    • Zhu, X., H. I. Suk, K. H. Thung, Y. Zhu, G. Wu, and D. Shen. “Joint discriminative and representative feature selection for alzheimer’s disease diagnosis.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10019 LNCS:77–85, 2016. https://doi.org/10.1007/978-3-319-47157-0_10.
       Full Text
    • Kim, J. W., H. I. Suk, J. P. Kim, and S. W. Lee. “Combined regression and classification approach for prediction of driver's braking intention.” In 3rd International Winter Conference on Brain Computer Interface, Bci 2015, 2015. https://doi.org/10.1109/IWW-BCI.2015.7073027.
       Full Text
    • Zhu, X., H. I. Suk, Y. Zhu, K. H. Thung, G. Wu, and D. Shen. “Multi-view classification for identification of Alzheimer’s disease.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9352:255–62, 2015. https://doi.org/10.1007/978-3-319-24888-2_31.
       Full Text
    • Lee, A. R., H. I. Suk, and S. W. Lee. “View-invariant 3D action recognition using spatiotemporal self-similarities from depth camera.” In Proceedings  International Conference on Pattern Recognition, 501–5, 2014. https://doi.org/10.1109/ICPR.2014.95.
       Full Text
    • Lee, D. G., H. I. Suk, and S. W. Lee. “Modeling crowd motions for abnormal activity detection.” In 11th Ieee International Conference on Advanced Video and Signal Based Surveillance, Avss 2014, 325–30, 2014. https://doi.org/10.1109/AVSS.2014.6918689.
       Full Text
    • Shi, Y., H. I. Suk, Y. Gao, and D. Shen. “Joint coupled-feature representation and coupled boosting for AD diagnosis.” In Proceedings of the Ieee Computer Society Conference on Computer Vision and Pattern Recognition, 2721–28, 2014. https://doi.org/10.1109/CVPR.2014.354.
       Full Text
    • Zhu, X., H. I. Suk, and D. Shen. “Matrix-similarity based loss function and feature selection for Alzheimer's disease diagnosis.” In Proceedings of the Ieee Computer Society Conference on Computer Vision and Pattern Recognition, 3089–96, 2014. https://doi.org/10.1109/CVPR.2014.395.
       Full Text
    • Li, Rongjian, Wenlu Zhang, Heung-Il Suk, Li Wang, Jiang Li, Dinggang Shen, and Shuiwang Ji. “Deep learning based imaging data completion for improved brain disease diagnosis.” In Med Image Comput Comput Assist Interv, 17:305–12, 2014. https://doi.org/10.1007/978-3-319-10443-0_39.
       Full Text  Link to Item
    • Suk, Heung-Ii, and Dinggang Shen. “Clustering-induced multi-task learning for AD/MCI classification.” In Med Image Comput Comput Assist Interv, 17:393–400, 2014. https://doi.org/10.1007/978-3-319-10443-0_50.
       Full Text  Link to Item
    • Zhu, Xiaofeng, Heung-Ii Suk, and Dinggang Shen. “A novel multi-relation regularization method for regression and classification in AD diagnosis.” In Med Image Comput Comput Assist Interv, 17:401–8, 2014. https://doi.org/10.1007/978-3-319-10443-0_51.
       Full Text  Link to Item
    • Kam, T. E., H. I. Suk, and S. W. Lee. “Non-homogeneous spatial filter optimization for EEG-based brain-computer interfaces.” In 2013 International Winter Workshop on Brain Computer Interface, Bci 2013, 26–28, 2013. https://doi.org/10.1109/IWW-BCI.2013.6506618.
       Full Text
    • Suk, H. I., and S. W. Lee. “A Bayesian approach for spatio-spectral filter optimization in BCI.” In 2013 International Winter Workshop on Brain Computer Interface, Bci 2013, 22–23, 2013. https://doi.org/10.1109/IWW-BCI.2013.6506616.
       Full Text
    • Yeom, S. K., H. I. Suk, and S. W. Lee. “EEG-based person authentication using face stimuli.” In 2013 International Winter Workshop on Brain Computer Interface, Bci 2013, 58–61, 2013. https://doi.org/10.1109/IWW-BCI.2013.6506630.
       Full Text
    • Jie, B., D. Zhang, H. I. Suk, C. Y. Wee, and D. Shen. “Integrating multiple network properties for MCI identification.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8184 LNCS:9–16, 2013. https://doi.org/10.1007/978-3-319-02267-3_2.
       Full Text
    • Lee, D. G., H. I. Suk, and S. W. Lee. “Crowd behavior representation using motion influence matrix for anomaly detection.” In Proceedings  2nd Iapr Asian Conference on Pattern Recognition, Acpr 2013, 110–14, 2013. https://doi.org/10.1109/ACPR.2013.30.
       Full Text
    • Liu, Feng, Heung-Il Suk, Chong-Yaw Wee, Huafu Chen, and Dinggang Shen. “High-order graph matching based feature selection for Alzheimer's disease identification.” In Med Image Comput Comput Assist Interv, 16:311–18, 2013. https://doi.org/10.1007/978-3-642-40763-5_39.
       Full Text  Link to Item
    • Liu, M., H. I. Suk, and D. Shen. “Multi-task sparse classifier for diagnosis of MCI conversion to AD with longitudinal MR images.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8184 LNCS:243–50, 2013. https://doi.org/10.1007/978-3-319-02267-3_31.
       Full Text
    • Suk, H. I., C. Y. Wee, and D. Shen. “Discriminative group sparse representation for mild cognitive impairment classification.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8184 LNCS:131–38, 2013. https://doi.org/10.1007/978-3-319-02267-3_17.
       Full Text
    • Suk, Heung-Il, and Dinggang Shen. “Deep learning-based feature representation for AD/MCI classification.” In Med Image Comput Comput Assist Interv, 16:583–90, 2013. https://doi.org/10.1007/978-3-642-40763-5_72.
       Full Text  Link to Item
    • Suk, H. I., Y. Wang, and S. W. Lee. “Online learning of sparse pseudo-input Gaussian process.” In Conference Proceedings  Ieee International Conference on Systems, Man and Cybernetics, 1357–60, 2012. https://doi.org/10.1109/ICSMC.2012.6377922.
       Full Text
    • Suk, H. I., and S. W. Lee. “A probabilistic approach to spatio-spectral filters optimization in Brain-Computer Interface.” In Conference Proceedings  Ieee International Conference on Systems, Man and Cybernetics, 19–24, 2011. https://doi.org/10.1109/ICSMC.2011.6083636.
       Full Text
    • Suk, H. I., and S. W. Lee. “Data-driven frequency bands selection in EEG-based brain-computer interface.” In Proceedings  International Workshop on Pattern Recognition in Neuroimaging, Prni 2011, 25–28, 2011. https://doi.org/10.1109/PRNI.2011.19.
       Full Text
    • Suk, H. I., and S. W. Lee. “Two-layer hidden Markov models for multi-class motor imagery classification.” In Proceedings  Workshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging, Wbd 2010  in Conjunction With Theinternational Conference on Pattern Recognition, Icpr 2010, 5–8, 2010. https://doi.org/10.1109/WBD.2010.16.
       Full Text
    • Suk, H. I., B. K. Sin, and S. W. Lee. “Analyzing human interactions with a network of dynamic probabilistic models.” In 2009 Workshop on Applications of Computer Vision, Wacv 2009, 2009. https://doi.org/10.1109/WACV.2009.5403108.
       Full Text
    • Suk, H. I., B. K. Sin, and S. W. Lee. “Recognizing hand gestures using dynamic bayesian network.” In 2008 8th Ieee International Conference on Automatic Face and Gesture Recognition, Fg 2008, 2008. https://doi.org/10.1109/AFGR.2008.4813342.
       Full Text
    • Suk, H. I., S. S. Cho, H. D. Yang, M. C. Roh, and S. W. Lee. “Real-time human-robot interaction based on continuous gesture spotting and recognition.” In 39th International Symposium on Robotics, Isr 2008, 120–23, 2008.
    • Suk, H. I., B. K. Sin, and S. W. Lee. “Robust modeling and recognition of hand gestures with dynamic Bayesian network.” In Proceedings  International Conference on Pattern Recognition, 2008. https://doi.org/10.1109/icpr.2008.4761337.
       Full Text
    • Suk, H. I., and B. K. Sin. “HMM-based gait recognition with human profiles.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4109 LNCS:596–603, 2006. https://doi.org/10.1007/11815921_65.
       Full Text

Some information on this profile has been compiled automatically from Duke databases and external sources. (Our About page explains how this works.) If you see a problem with the information, please write to Scholars@Duke and let us know. We will reply promptly.