AI-Med Lab. @ GIST

[1] S. Lee, J. Youn, H. Kim, M. Kim*, S. H. Yoon*, "CXR-LLAVA: a multimodal large language model for interpreting chest X-ray images"  https://arxiv.org/abs/2310.18341 

[28] S. Kim, Mansu Kim, J.-e. Lee, B.-y. Park*, H. Park* “Prognostic model for predicting Alzheimer’s disease conversion using functional connectivity manifolds,” Alzheimers Research & Therapy, 2024, accepted  (IF: 7.9, Top 4.2%)

[27] J. Kim†, Mansu Kim†, H. Park* “Domain Aware Multi-Task Pretraining of 3D Swin Transformer for T1- weighted Brain MRI,” Asian Conference on Computer Vision (ACCV) , 2024

[26] .H. Kim, S.W. Seo, Y.H. Park, J. Kim, H.J. Kim, H. Jang, J. Yun, Mansu Kim*, J. Kim*, “Clinical application of sparse canonical correlation analysis to detect genetic associations with cortical thickness in Alzheimer’s disease,” Frontiers in Neuroscience, 2024, DOI: 10.3389/fnagi.2022.781883

[25] K.T. Barnhart, K.J. Bollig, S. Senapati, P. Takacs, J.C. Robins, D.J. Haisenleder, L.A.Beer, R.F. Savaris, N.C. Koelper, D.W. Speicher, J. Chittams, J. Bao, Z. Wen, Y. Feng, Mansu Kim, S. Mumford, L. Shen, P. Gimotty*, “Mul- tiplexed Serum Biomarkers to Discriminate Nonviable and Ectopic Pregnancy,” Fertility and Sterility, 2024, DOI: 10.1016/j.fertnstert.2024.04.028 (IF: 6.6, Top 2.6%)

[24] Bao, B.N. Lee, J. Wen, Mansu Kim, S. Yang, C. Davatzikos, Q. Long, M.D. Ritchie, L. Shen*, “Employing informatics strategies in Alzheimer’s disease research: A review from genetics, multi-omics, and biomarkers to clinical outcomes,” Annual Review of Biomedical Data Science, 2024, DOI: 10.1146/annurev-biodatasci-102423- 121021 (IF: 7.0, Top 2.3%)

[23] J. Youn, D.W. Kang, H.K. Lim, Mansu Kim*, “Brain-Aware Readout Layers in GNNs: Advancing Alzheimer’s early Detection and Neuroimaging,” IJCAI workshop on Human Brain and Artificial Intelligence, 2024  [PDF] [Code]

[21] .H. Kim, H.W. Lee, H. Ham, H.J. Kim, H. Jang, J.P. Kim, Y.H. Park, Mansu Kim*, S.W. Seo*, “Clinical effects of novel susceptibility genes for beta-amyloid: a gene-based association study in the Korean population,” Frontiers in Aging Neuroscience, 2023, DOI: 10.3389/fnagi.2023.1278998

[21] Mansu Kim, R. Wu, X. Yao, A.J. Saykin, J.H. Moore, Q. Long. L. Shen*, “ Identifying genetic markers enriched by brain imaging endophenotypes in Alzheimer’s disease,” BMC Med Genomics, 2022, DOI: 10.1186/s12920-022- 01323-8 

[20] J. Baik†, Mansu Kim†, J. Bao, Q. Long, L. Shen*, “Identifying Alzheimer’s genes via brain transcriptome mapping,” BMC Med Genomics, 2022, DOI: 10.1186/s12920-022-01260-6

[19] J. Youn†, Mansu Kim†, J.S. Kim, H. Park*, J.W. Cho*, “Pallidal Structural Changes Related with Levodopa- induced Dyskinesia in Parkinson’s disease,” Frontiers in Aging Neuroscience, 2022, DOI: 10.3389/fnagi.2022.78188

[18] Mansu Kim, E.J. Min, K. Liu, J. Yan, A.J. Saykin, J.H. Moore, Q. Long, L. Shen*, “Multi-task learning based structured sparse canonical correlation analysis for brain imaging genetics,” Medical Image Analysis, 2022, DOI: 10.1016/j.media.2021.102297 (IF: 13.828, Top 1.4%)

[17] B.-y. Park, H. Park, F. Morys, Mansu Kim, K. Byeon, H. Lee, S.H. Kim, S.L. Valk, A. Dagher, B.C. Bernhardt*, “Inter-individual body mass variations relate to fractionated functional brain hierarchies,” Communications Biology, 2021, DOI: 10.1038/s42003-021-02268-x (IF: 6.268, Top 8.1%)

[16] Mansu Kim, J. Bao, K. Liu, B.-y. Park, H. Park, J. Baik, L. Shen*, “A structural enriched functional network: An application to predict brain cognitive performance,” Medical Image Analysis, 2021, DOI: 10.1016/j.media.2021.1020 26 (IF: 8.545, Top 4.9%)

[15] Mansu Kim, J. Bao, K. Liu, B.-y. Park, H. Park, L. Shen*, “Structural connectivity enriched functional brain network using simplex regression with GraphNet,” Machine learning in medical imaging," 2020, DOI: 10.1007/978- 3-030-59861-7_30

[14] Q. Sun, Z. Huang, Mansu Kim, A. Hara, G. Maupome, and L. Shen*, “Identifying Hard-Tissue Conditions from Dental Images using Convolutional Neural Network,” IEEE ISBI, 2020

[13] Mansu Kim, M. Kim, J. H. Won, J. Hong, J. Kwon, H. Park, and L. Shen*, “Deep network-based feature selection for imaging genetics: application to identifying biomarkers for Parkinson’s disease,” IEEE ISBI, 2020 DOI: 10.1109/isbi45749.2020.9098471

[12] Mansu Kim†, J.S. Kim†, J. Youn, H. Park, J.W. Cho*, “GraphNet-based imaging biomarker model to explain levodopa-induced dyskinesia in Parkinson’s disease,” Computer Methods and Programs in Biomedicine, 2020, DOI: 10.1016/j.cmpb.2020.105713 (IF: 3.632, Top 14.4%)

[11] H. Lee, B.-y. Park, K. Byeon, J.H. Won, Mansu Kim, S.H. Lee, H. Park*, “Multivariate association be- tween brain function and eating disorders using sparse canonical correlation analysis,” Plos one, 2020, DOI: jour- nal.pone.0237511

[10] J.H. Won, Mansu Kim, J. Youn, H. Park*, “prediction of age at onset in parkinson’s disease using objective specific neuroimaging genetics based on a sparse canonical correlation analysis,” Scientific Reports, 2020, DOI: 10.1038/s41598-020-68301-x

[9] Mansu Kim, J.H. Won, J. Youn, H. Park*, “Joint-connectivity-based sparse canonical correlation analysis of imaging genetics for detecting biomarkers of Parkinson’s disease,” IEEE transactions on medical imaging, 2020, DOI: 10.1109/TMI.2019.2918839 (IF: 6.685, Top 2.3%)

[8] J.H. Won, Mansu Kim, B.-y. Park, J. Youn, H. Park*, “Effectiveness of imaging genetics analysis to explain degree of depression in Parkinson’s disease,” Plos one, 2019, DOI: 10.1371/journal.pone.0211699

[7] b.-y. Park, M.J. Lee, Mansu Kim, S.H. Lee, H. Park*, “Structural and functional brain connectivity changes be- tween people with abdominal and non-abdominal obesity and their association with behaviors of eating disorders,” Frontiers in neuroscience, 2018, DOI: 10.3389/fnins.2018.00741 

[6] Mansu Kim, J. Kim, S.H. Lee, H. Park*, “Imaging genetics approach to Parkinson’s disease and its correlation with clinical score,” Scientific reports, 2017, DOI: 10.1038/srep46700 (IF: 4.259, Top 14.8%) 

[5] S.J. Son, Mansu Kim, H. Park*, “Imaging analysis of Parkinson’s disease patients using SPECT and tractogra- phy,” Scientific reports, 2016, DOI: 10.1038/srep38070 (IF: 5.228, Top 10.3%) 

[4] Mansu Kim, H. Park*, “Structural connectivity profile of scans without evidence of dopaminergic deficit (SWEDD) patients compared to normal controls and Parkinson’s disease patients,” Parkinson’s Disease, 2016, DOI: 10.1155/2016/8704910 

[3] B.-y. Park, Mansu Kim, J. Seo, J.M. Lee, H. Park*, “Connectivity analysis and feature classification in attention deficit hyperactivity disorder sub-types: a task functional magnetic resonance imaging study,” Brain topography, 2016, DOI: 10.1007/s10548-015-0463-1 

[2] Mansu Kim, H. Park*, “Using tractography to distinguish SWEDD from Parkinson’s disease patients based on connectivity,” Parkinson’s Disease, 2016, DOI: 10.1155/2016/8704910 

[1] S.H. Lee, Mansu Kim, H. Park*, “Planning for selective amygdalohippocampectomy involving less neu- ronal fiber damage based on brain connectivity using tractography,” Neural Regeneration Research, 2015,DOI: 0.4103/1673-5374.160104