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Conference papers

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  1. Machado-Reyes D, Kim M, Chao H, Hahn J, Shen L, Yan P. (2022) Genomics transformer for diagnosing Parkinson's disease. BHI’22: The IEEE International Conference on Biomedical and Health Informatics, in press, Ioannina, Greece, September 27-30, 2022.
     

  2. Machado-Reyes D, Kim M, Chao H, Shen L, Yan P. (2022) Connectome transformer with anatomically inspired attention for Parkinson’s diagnosis. ACM-BCB’22: The ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, in press, Chicago, August 7-10, 2022.
     

  3. Bao J*, Wen Z*, Kim M, Zhao X, Lee BN, Jung SH, Davatzikos C, Saykin AJ, Thompson PM, Kim D, Zhao Y, Shen L, for the ADNI. (2022) Identifying highly heritable brain amyloid phenotypes through mining Alzheimer's imaging and sequencing biobank data. Pac Symp Biocomput. 2022;27:109-20. (* Equal Contribution)
     

  4. Bao J*, Wen Z*, Kim M, Saykin AJ, Thompson PM, Zhao Y, Shen L, for the ADNI. (2022) Identifying imaging genetic associations via regional morphometricity estimation. Pac Symp Biocomput. 2022;27:97-108. (* Equal Contribution)
     

  5. Kim M, Kim J, Qu J, Huang H, Sohn KA, Long Q, Kim D, Shen L. (2021) Interpretable temporal graph neural network for prognostic prediction of Alzheimer’s disease using longitudinal neuroimaging data. BIBM’16: IEEE Int. Conf. on Bioinformatics and Biomedicine, pp. 1381-1384, Virtual Conference, Dec 9-12, 2021. [20% acceptance rate]
     

  6. Zhao Y, Zhao X, Kim M, Bao J, Shen L. (2021) A novel Bayesian semi-parametric model for learning heritable imaging traits. MICCAI’21: Med Image Comput Comput Assist Interv, Lecture Notes in Computer Science, in press, Virtual Conference, Sep 27-Oct 1, 2021. [33% acceptance rate]
     

  7. Feng Y, Kim M, Yao X, Liu K, Long Q, Shen L. (2020) Deep multiview learning for population subtyping with multimodal imaging. BIBE’20: IEEE Int. Conf. on BioInformatics and BioEngineering, pp 308-314, Virtual Conference, October 26-28, 2020 USA.
     

  8. Bao J, Kim M, Sun Q, Hara A, Maupome G, Shen L. (2020) Estimating hard-tissue conditions from dental images via machine learning. BIBE’20: IEEE Int. Conf. on BioInformatics and BioEngineering, pp 315-322, Virtual Conference, October 26-28, 2020 USA.
     

  9. Kim M, Bao J, Liu K, Park B, Park H, Shen L. (2020) Structural connectivity enriched functional brain network using simplex regression with GraphNet. MLMI’20: Machine Learning in Medical Imaging, Lecture Notes in Computer Science, 12436: 292-302, Virtual Conference, October 4, 2020.
     

  10. Kim M, Won JH, Hong J, Kwon J, Park H, Shen L. (2020) Deep network-based feature selection for imaging genetics: Application to identifying biomarkers for Parkinson’s disease. ISBI’20: IEEE Int Sym on Biomedical Imaging, pp 1920-1923, April 3-7, 2020; Iowa City, IA.
     

  11. Won JH, Kim M, Yoon J, Park H. (2019) Subtype identification of Parkinson’s disease using sparse canonical correlation and clustering analysis of multimodal neuroimaging. MTSR'19: Int Con on Metadata and Semantics Research, pp 126-136, October 28-31, 2019; Rome, Italy. 
     

  12. Kim M, Son S-J, Park H. (2017) Imaging Genetics Approach to Predict Progression of Parkinson’s Diseases. EMBC'17: IEEE Engineering in Medicine and Biology Society, pp 3922-3925, July 11-15, 2017, Jeju, Rep. of Korea. [Oral presentation]

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