Posts by Collection

portfolio

publications

Published in , 1900

Published in , 1900

Published in , 1900

Published in , 1900

[Conference] Structural Connectivity Enriched Functional Brain network using Simplex Regression with GraphNet

Published in MICCAI-MLMI, 2020

We proposed a simplex regression model with graph-constrained Elastic Net (GraphNet) to estimate functional networks enriched by structural connectivity in a biologically meaningful way with a low model complexity.

Citation: Mansu Kim, Jingxaun Bao, Kefei Liu, Bo-yong Park, Hyunjin Park, Li Shen. (2020). "Structural Connectivity Enriched Functional Brain network using Simplex Regression with GraphNet." International Conference on Medical Image Computing & Computer Assisted Intervention - Machine Learning in Medical Imaging Workshop.

[Conference] Estimating Hard-tissue Conditions from Dental Images via Machine Learning

Published in The 20th International Conference on BioInformatics and BioEngineering (ieeeBIBE2020), 2020

We applied four categories of machine learning strategies including nine different methods with two different feature representations to estimate the probability and severity of dental hard-tissue conditions from photographic tooth images.

Citation: Jingxuan Bao, Mansu Kim, Qing Sun, Anderson T. Hara, Gerardo Maupome, Li Shen. (2020). "Estimating Hard-tissue Conditions from Dental Images via Machine Learning." 20th International Conference on BioInformatics and BioEngineering (ieeeBIBE).

[Journal] A Structural Enriched Functional Network: An Application to Predict Brain Cognitive Performance

Published in Medical Image Analysis, 2020

This paper proposed a method to accurately estimate the brain functional network enriched by the structural network from diffusion magnetic resonance imaging.

Citation: Mansu Kim, Jingxaun Bao, Kefei Liu, Bo-yong Park, Hyunjin Park, Jae Young Baik, Li Shen. (2020). "A Structural Enriched Functional Network: An Application to Predict Brain Cognitive Performance." Medical Image Analysis.

[Abstract] Mining brain-wide gene expression data to identify imaging genomic modules via biclustering

Published in Organization for Human Brain Mapping, 2021

Mining brain-wide gene expression data to identify imaging genomic modules via biclustering.

Citation: Jingxuan Bao, Mansu Kim, Xiaohui Yao, Trang Le, Patryk Orzechowski, Jingwen Yan, Andrew Saykin, Jason Moore, Li Shen. (2021). "Mining brain-wide gene expression data to identify imaging genomic modules via biclustering." Organization for Human Brain Mapping 2021.

[Conference] Identifying imaging genetic associations via regional morphometricity estimation

Published in PSB, 2022

We propose a novel framework to identify the SNP-ROI association via regional morphometricity estimation of each studied single nucleotide polymorphism (SNP).

Citation: Jingxuan Bao, Zixuan Wen, Mansu Kim, Andrew J. Saykin, Paul M. Thompson, Yize Zhao, Li Shen, and for the Alzheimer’s Disease Neuroimaging Initiative. (2022). "Identifying imaging genetic associations via regional morphometricity estimation." Pacific Symposium on Biocomputing.

[Conference, keynote presenter, travel award] Identifying highly heritable brain amyloid phenotypes through mining Alzheimer’s imaging and sequencing biobank data

Published in PSB, 2022

We propose a novel method to define highly heritable brain regions.

Citation: Jingxuan Bao, Zixuan Wen, Mansu Kim, Brain N. Lee, Sang-Hyuk Jung, Christos Davatzikos, Andrew J. Saykin, Paul M. Thompson, Dokyoon Kim, Yize Zhao, Li Shen, and for the Alzheimer’s Disease Neuroimaging Initiative. (2021). "Identifying highly heritable brain amyloid phenotypes through mining Alzheimer’s imaging and sequencing biobank data." Pacific Symposium on Biocomputing.

[Journal] Identifying Alzheimer’s genes via brain transcriptome mapping

Published in BMC Medical Genomics, 2022

We proposed a novel disease-related brain transcriptomic mapping method to identify genes whose expression profiles spatially correlated with regional diagnostic effects on a studied brain trait.

Citation: Baik, J.Y., Kim, M., Bao, J., et al. (2022). "Identifying Alzheimer’s genes via brain transcriptome mapping." BMC Med Genomics.

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.