Kim‐Han Thung - Concepedia

Author

Kim‐Han Thung

University of North Carolina at Chapel Hill ORCID

Also Known As

K. H. Thung, K.-H. Thung, Kim Han Thung, Kim Thung, Kim-Han Thung, Kimhan Thung, Kim‐Han Thung, Li, Gang, Li, Guoshi, Lin, Weili

106

Publications

Citations

H-Index

Concepts

All Affiliations

University of North Carolina at Chapel Hill Korea University Imaging Center University of Malaya Shanghai Jiao Tong University

About

Kim‐Han Thung is an author at University of North Carolina at Chapel Hill specializing in engineering, neuroimaging, and neuroscience.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	17	21	1.6K
2	Medicine	16	18	1.5K
3	Health Sciences	6	6	250
4	Business	1	1	15
5	Education	1	1	13

Kim‐Han Thung

Publications

2.5K

Citations

H-Index

Page 1

	Year	Citations
A Robust Deep Model for Improved Classification of AD/MCI Patients Feng Li, Loc Tran, Kim‐Han Thung, IEEE Journal of Biomedical and Health Informatics Convolutional Neural NetworkEngineeringMachine LearningAutoencodersDiagnosis	2015	297
Effective feature learning and fusion of multimodality data using stage‐wise deep neural network for dementia diagnosis Tao Zhou, Kim‐Han Thung, Xiaofeng Zhu, Human Brain Mapping EngineeringMachine LearningMultimodal LearningDementia DiagnosisLongitudinal Neuroimaging	2018	257
Latent Representation Learning for Alzheimer’s Disease Diagnosis With Incomplete Multi-Modality Neuroimaging and Genetic Data Tao Zhou, Mingxia Liu, Kim‐Han Thung, IEEE Transactions on Medical Imaging EngineeringMachine LearningMagnetic Resonance ImagingLatent ModelingAlzheimer's Disease	2019	216
A survey of image quality measures Kim‐Han Thung, Raveendran Paramesran Total Quality ManagementImage AnalysisEngineeringQuality MetricVideo Quality	2009	203
Benchmark on Automatic Six-Month-Old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge Li Wang, Dong Nie, Guannan Li, IEEE Transactions on Medical Imaging	2019	191
Longitudinal clinical score prediction in Alzheimer's disease with soft-split sparse regression based random forest Lei Huang, Yan Jin, Yaozong Gao, Neurobiology of Aging Neuroimaging BiomarkersAlzheimer's DiseaseMedicineDementiaPredictive Analytics	2016	114
Multi-modal latent space inducing ensemble SVM classifier for early dementia diagnosis with neuroimaging data Tao Zhou, Kim‐Han Thung, Mingxia Liu, Medical Image Analysis Neuroimaging BiomarkersMulti-modal Latent SpaceNeuropsychologyAlzheimer's DiseaseNeuroimaging Modality	2019	103
Neurodegenerative disease diagnosis using incomplete multi-modality data via matrix shrinkage and completion Kim‐Han Thung, Chong-Yaw Wee, Pew‐Thian Yap, NeuroImage Neuroimaging BiomarkersNeurodegenerative DiseasesEngineeringNeurodegenerative Disease DiagnosisNeuroimaging Modality	2014	97
Conversion and time-to-conversion predictions of mild cognitive impairment using low-rank affinity pursuit denoising and matrix completion Kim‐Han Thung, Pew‐Thian Yap, Ehsan Adeli, Medical Image Analysis Time-to-conversion PredictionsNeuroimaging BiomarkersNeuropsychologySparse RepresentationMatrix Factorization	2018	92
Identification of infants at high‐risk for autism spectrum disorder using multiparameter multiscale white matter connectivity networks Yan Jin, Chong‐Yaw Wee, Feng Shi, Human Brain Mapping	2015	91

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