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  • Li Shen
2018

A Review of Statistical-learning Imaging Genetics

Hao, X. K., Li, C. X., Yan, J. W., Shen, L. & Zhang, D. Q., Jan 2018, In : Zidonghua Xuebao/Acta Automatica Sinica. 44, 1, p. 13-24 12 p.

Research output: Contribution to journalReview article

2017

New probabilistic multi-graph decomposition model to identify consistent human brain network modules

Luo, D., Huo, Z., Wang, Y., Saykin, A., Shen, L. & Huang, H., Jan 31 2017, Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016. Institute of Electrical and Electronics Engineers Inc., p. 301-310 10 p. 7837854

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Imaging genomics

Shen, L. & Cooper, L. A. D., Jan 1 2017, PACIFIC SYMPOSIUM ON BIOCOMPUTING 2017. 212679 ed. World Scientific Publishing Co. Pte Ltd, p. 51-57 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

BECA: A Software Tool for Integrated Visualization of Human Brain Data

Li, H., Fang, S., Zigon, B., Sporns, O., Saykin, A. J., Goñi, J. & Shen, L., Jan 1 2017, Brain Informatics - International Conference, BI 2017, Proceedings. Zeng, Y., Xu, B., Martone, M., He, Y., Peng, H., Luo, Q. & Kotaleski, J. H. (eds.). Springer Verlag, p. 285-291 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10654 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Longitudinal genotype-phenotype association study via temporal structure auto-learning predictive model

The ADNI, Jan 1 2017, Research in Computational Molecular Biology - 21st Annual International Conference, RECOMB 2017, Proceedings. Sahinalp, S. C. (ed.). Springer Verlag, p. 287-302 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10229 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Predicting interrelated Alzheimer’s disease outcomes via new self-learned structured low-rank model

Wang, X., Liu, K., Yan, J., Risacher, S. L., Saykin, A. J., Shen, L. & Huang, H., Jan 1 2017, Information Processing in Medical Imaging - 25th International Conference, IPMI 2017, Proceedings. Zhu, H., Niethammer, M., Styner, M., Zhu, H., Shen, D., Yap, P-T., Aylward, S. & Oguz, I. (eds.). Springer Verlag, p. 198-209 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10265 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

A fast SCCA algorithm for big data analysis in brain imaging genetics

Alzheimer’s Disease Neuroimaging Initiative, 2017, Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - 1st International Workshop, GRAIL 2017 6th International Workshop, MFCA 2017 and 3rd International Workshop, MICGen 2017 Held in Conjunction with MICCAI 2017, Proceedings. Springer Verlag, Vol. 10551 LNCS. p. 210-219 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10551 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations
2019

A dirty multi-task learning method for multi-modal brain imaging genetics

for the Alzheimer’s Disease Neuroimaging Initiative, Jan 1 2019, Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings. Shen, D., Yap, P-T., Liu, T., Peters, T. M., Khan, A., Staib, L. H., Essert, C. & Zhou, S. (eds.). Springer, p. 447-455 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11767 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2017

Sparse Canonical Correlation Analysis via truncated ℓ1-norm with application to brain imaging genetics

Du, L., Zhang, T., Liu, K., Yao, X., Yan, J., Risacher, S. L., Guo, L., Saykin, A. & Shen, L., Jan 17 2017, Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016. Institute of Electrical and Electronics Engineers Inc., p. 707-711 5 p. 7822605

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations
2019

Mining regional imaging genetic associations via voxel-wise enrichment analysis

Yao, X., Cong, S., Yan, J., Risacher, S. L., Saykin, A. J., Moore, J. H. & Shen, L., May 2019, 2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 8834450. (2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations
2016

Structured sparse canonical correlation analysis for brain imaging genetics: An improved GraphNet method

Du, L., Huang, H., Yan, J., Kim, S., Risacher, S. L., Inlow, M., Moore, J. H., Saykin, A. J. & Shen, L., May 15 2016, In : Bioinformatics. 32, 10, p. 1544-1551 8 p.

Research output: Contribution to journalArticle

35 Scopus citations
2017

Mining outcome-relevant brain imaging genetic associations via three-way sparse canonical correlation analysis in Alzheimer's disease

Hao, X., Li, C., Du, L., Yao, X., Yan, J., Risacher, S. L., Saykin, A., Shen, L. & Zhang, D., Mar 14 2017, In : Scientific Reports. 7, 44272.

Research output: Contribution to journalArticle

7 Scopus citations
2018

Bootstrapped Sparse Canonical Correlation Analysis: Mining Stable Imaging and Genetic Associations With Implicit Structure Learning. Mining Stable Imaging and Genetic Associations With Implicit Structure Learning.

Yan, J., Du, L., Kim, S., Risacher, S. L., Huang, H., Inlow, M., Moore, J. H., Saykin, A. J. & Shen, L., Jan 1 2018, Imaging Genetics. Elsevier Inc., p. 101-117 17 p.

Research output: Chapter in Book/Report/Conference proceedingChapter

2016

Network-based analysis of genetic variants associated with hippocampal volume in Alzheimer's disease: A study of ADNI cohorts

Song, A., Yan, J., Kim, S., Risacher, S. L., Wong, A. K., Saykin, A. J., Shen, L. & Greene, C. S., Jan 19 2016, In : BioData Mining. 9, 1, 3.

Research output: Contribution to journalArticle

14 Scopus citations

Identifying Multimodal Intermediate Phenotypes Between Genetic Risk Factors and Disease Status in Alzheimer’s Disease

Hao, X., Yao, X., Yan, J., Risacher, S. L., Saykin, A. J., Zhang, D., Shen, L. & for the Alzheimer’s Disease Neuroimaging Initiative, T. A. D. N. I., Oct 1 2016, In : Neuroinformatics. 14, 4, p. 439-452 14 p.

Research output: Contribution to journalArticle

11 Scopus citations
2020

A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease

Liu, M., Li, F., Yan, H., Wang, K., Ma, Y., Shen, L. & Xu, M., Mar 2020, In : NeuroImage. 208, 116459.

Research output: Contribution to journalArticle

Open Access
2019

Identifying imaging markers for predicting cognitive assessments using wasserstein distances based matrix regression

Yan, J., Deng, C., Luo, L., Wang, X., Yao, X., Shen, L. & Huang, H., Jan 1 2019, In : Frontiers in Neuroscience. 13, JUL, 668.

Research output: Contribution to journalArticle

Open Access
2017

Brain explorer for connectomic analysis

for the Alzheimer’s Disease Neuroimaging Initiative, Dec 1 2017, In : Brain Informatics. 4, 4, p. 253-269 17 p.

Research output: Contribution to journalArticle

1 Scopus citations
2019

Joint between-sample normalization and differential expression detection through 0-regularized regression

Liu, K., Shen, L. & Jiang, H., Dec 2 2019, In : BMC Bioinformatics. 20, 593.

Research output: Contribution to journalArticle

Open Access

Statistical inference on the number of cycles in brain networks

Chung, M. K., Huang, S. G., Gritsenko, A., Shen, L. & Lee, H., Apr 2019, ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, p. 113-116 4 p. 8759222. (Proceedings - International Symposium on Biomedical Imaging; vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Fast Multi-Task SCCA Learning with Feature Selection for Multi-Modal Brain Imaging Genetics

Du, L., Liu, K., Yao, X., Risacher, S. L., Han, J., Guo, L., Saykin, A. & Shen, L., Jan 21 2019, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. Schmidt, H., Griol, D., Wang, H., Baumbach, J., Zheng, H., Callejas, Z., Hu, X., Dickerson, J. & Zhang, L. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 356-361 6 p. 8621298. (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations
2017

Genome-wide association and interaction studies of CSF T-tau/Aβ42 ratio in ADNI cohort

Li, J., Zhang, Q., Chen, F., Meng, X., Liu, W., Chen, D., Yan, J., Kim, S., Wang, L., Feng, W., Saykin, A. J., Liang, H. & Shen, L., Sep 2017, In : Neurobiology of Aging. 57, p. 247.e1-247.e8

Research output: Contribution to journalArticle

10 Scopus citations

Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort

for the Alzheimer's Disease Neuroimaging Initiative, May 30 2017, In : BMC genomics. 18, 1, 421.

Research output: Contribution to journalArticle

5 Scopus citations
2019

Genome-wide network-assisted association and enrichment study of amyloid imaging phenotype in alzheimer’s disease

Alzheimer’s Disease Neuroimaging Initiative, Jan 1 2019, In : Current Alzheimer research. 16, 13, p. 1163-1174 12 p.

Research output: Contribution to journalArticle

1 Scopus citations
2016

Association between anticholinergic medication use and cognition, brain metabolism, and brain atrophy in cognitively normal older adults

Alzheimer's Disease Neuroimaging Initiative, Jun 2016, In : JAMA Neurology. 73, 6, p. 721-732 12 p.

Research output: Contribution to journalArticle

92 Scopus citations
2017

Pattern Discovery in Brain Imaging Genetics via SCCA Modeling with a Generic Non-convex Penalty

Du, L., Liu, K., Yao, X., Yan, J., Risacher, S. L., Han, J., Guo, L., Saykin, A. J., Shen, L., Weiner, M. W., Aisen, P., Petersen, R., Jack, C. R., Jagust, W., Trojanowki, J. Q., Toga, A. W., Beckett, L., Green, R. C., Morris, J., Shaw, L. M. & 293 others, Khachaturian, Z., Sorensen, G., Carrillo, M., Kuller, L., Raichle, M., Paul, S., Davies, P., Fillit, H., Hefti, F., Holtzman, D., Mesulam, M. M., Potter, W., Snyder, P., Schwartz, A., Montine, T., Thomas, R. G., Donohue, M., Walter, S., Gessert, D., Sather, T., Jiminez, G., Balasubramanian, A. B., Mason, J., Sim, I., Harvey, D., Bernstein, M., Fox, N., Thompson, P., Schuff, N., Decarli, C., Borowski, B., Gunter, J., Senjem, M., Vemuri, P., Jones, D., Kantarci, K., Ward, C., Koeppe, R. A., Foster, N., Reiman, E. M., Chen, K., Mathis, C., Landau, S., Cairns, N. J., Franklin, E., Taylor-Reinwald, L., Lee, V., Korecka, M., Figurski, M., Crawford, K., Neu, S., Foroud, T. M., Potkin, S., Faber, K., Kim, S., Nho, K., Thal, L., Buckholtz, N., Albert, M., Frank, R., Hsiao, J., Kaye, J., Quinn, J., Silbert, L., Lind, B., Carter, R., Dolen, S., Schneider, L. S., Pawluczyk, S., Beccera, M., Teodoro, L., Spann, B. M., Brewer, J., Vanderswag, H., Fleisher, A., Heidebrink, J. L., Lord, J. L., Mason, S. S., Albers, C. S., Knopman, D., Johnson, K., Doody, R. S., Villanueva-Meyer, J., Pavlik, V., Shibley, V., Chowdhury, M., Rountree, S., Dang, M., Stern, Y., Honig, L. S., Bell, K. L., Ances, B., Carroll, M., Creech, M. L., Franklin, E., Mintun, M. A., Schneider, S., Oliver, A., Marson, D., Geldmacher, D., Love, M. N., Griffith, R., Clark, D., Brockington, J., Roberson, E., Grossman, H., Mitsis, E., Shah, R. C., Detoledo-Morrell, L., Duara, R., Greig-Custo, M. T., Barker, W., Onyike, C., D'Agostino, D., Kielb, S., Sadowski, M., Sheikh, M. O., Ulysse, A., Gaikwad, M., Murali Doraiswamy, P., Petrella, J. R., Borges-Neto, S., Wong, T. Z., Coleman, E., Arnold, S. E., Karlawish, J. H., Wolk, D. A., Clark, C. M., Smith, C. D., Jicha, G., Hardy, P., Sinha, P., Oates, E., Conrad, G., Lopez, O. L., Oakley, M. A., Simpson, D. M., Porsteinsson, A. P., Goldstein, B. S., Martin, K., Makino, K. M., Ismail, M. S., Brand, C., Preda, A., Nguyen, D., Womack, K., Mathews, D., Quiceno, M., Levey, A. I., Lah, J. J., Cellar, J. S., Burns, J. M., Swerdlow, R. H., Brooks, W. M., Apostolova, L., Tingus, K., Woo, E., Silverman, D. H. S., Lu, P. H., Bartzokis, G., Graff-Radford, N. R., Parfitt, F., Poki-Walker, K., Farlow, M. R., Marie Hake, A., Matthews, B. R., Brosch, J. R., Herring, S., Van Dyck, C. H., Carson, R. E., MacAvoy, M. G., Varma, P., Chertkow, H., Bergman, H., Hosein, C., Black, S., Stefanovic, B., Caldwell, C., Robin Hsiung, G. Y., Mudge, B., Sossi, V., Feldman, H., Assaly, M., Finger, E., Pasternack, S., Rachisky, I., Rogers, J., Trost, D., Kertesz, A., Bernick, C., Munic, D., Rogalski, E., Lipowski, K., Weintraub, S., Bonakdarpour, B., Kerwin, D., Wu, C. K., Johnson, N., Sadowsky, C., Villena, T., Scott Turner, R., Johnson, K., Reynolds, B., Sperling, R. A., Johnson, K. A., Marshall, G., Yesavage, J., Taylor, J. L., Lane, B., Rosen, A., Tinklenberg, J., Sabbagh, M. N., Belden, C. M., Jacobson, S. A., Sirrel, S. A., Kowall, N., Killiany, R., Budson, A. E., Norbash, A., Lynn Johnson, P., Obisesan, T. O., Wolday, S., Allard, J., Lerner, A., Ogrocki, P., Tatsuoka, C., Fatica, P., Fletcher, E., Maillard, P., Olichney, J., Decarli, C., Carmichael, O., Kittur, S., Borrie, M., Lee, T. Y., Bartha, R., Johnson, S., Asthana, S., Carlsson, C. M., Tariot, P., Burke, A., Milliken, A. M., Trncic, N., Fleisher, A., Reeder, S., Bates, V., Capote, H., Rainka, M., Scharre, D. W., Kataki, M., Kelly, B., Zimmerman, E. A., Celmins, D., Brown, A. D., Pearlson, G. D., Blank, K., Anderson, K., Flashman, L. A., Seltzer, M., Hynes, M. L., Santulli, R. B., Sink, K. M., Gordineer, L., Williamson, J. D., Garg, P., Watkins, F., Ott, B. R., Tremont, G., Daiello, L. A., Salloway, S., Malloy, P., Correia, S., Rosen, H. J., Miller, B. L., Perry, D., Mintzer, J., Spicer, K., Bachman, D., Pomara, N., Hernando, R., Sarrael, A., Schultz, S. K., Ekstam Smith, K., Koleva, H., Nam, K. W., Shim, H., Relkin, N., Chaing, G., Lin, M., Ravdin, L., Smith, A., Ashok Raj, B. & Fargher, K., Dec 1 2017, In : Scientific reports. 7, 1, 14052.

Research output: Contribution to journalArticle

3 Scopus citations

Identification of discriminative imaging proteomics associations in Alzheimer’s disease via a novel sparse correlation model

Alzheimer's Disease Neuroimaging Initiative, Jan 1 2017, In : Pacific Symposium on Biocomputing. 0, 212679, p. 94-104 11 p.

Research output: Contribution to journalConference article

Open Access
3 Scopus citations

Pattern Discovery from Directional High-Order Drug-Drug Interaction Relations

Ning, X., Schleyer, T., Shen, L. & Li, L., Sep 8 2017, Proceedings - 2017 IEEE International Conference on Healthcare Informatics, ICHI 2017. Cummins, M., Facelli, J., Meixner, G., Giraud-Carrier, C. & Nakajima, H. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 154-162 9 p. 8031143. (Proceedings - 2017 IEEE International Conference on Healthcare Informatics, ICHI 2017).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Association analysis of rare variants near the APOE region with CSF and neuroimaging biomarkers of Alzheimer’s disease

Nho, K., Kim, S., Horgusluoglu, E., Risacher, S. L., Shen, L., Kim, D., Lee, S., Foroud, T., Shaw, L. M., Trojanowski, J. Q., Aisen, P. S., Petersen, R. C., Jack, C. R., Weiner, M. W., Green, R. C., Toga, A. W. & Saykin, A. J., May 24 2017, In : BMC Medical Genomics. 10, 29.

Research output: Contribution to journalArticle

9 Scopus citations

Association of plasma neurofilament light with neurodegeneration in patients with Alzheimer disease

Alzheimer's Disease Neuroimaging Initiative, May 2017, In : JAMA Neurology. 74, 5, p. 557-566 10 p.

Research output: Contribution to journalArticle

164 Scopus citations
2016

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

The Alzheimer's Disease Neuroimaging Initiative, Jun 21 2016, In : Nature communications. 7, 11934.

Research output: Contribution to journalArticle

249 Scopus citations
2018

Imaging genomics

Huang, H., Shen, L., Thompson, P. M., Huang, K., Huang, J. & Yang, L., Jan 1 2018, PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018. 212669 ed. World Scientific Publishing Co. Pte Ltd, p. 304-306 3 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations
2019

Type 2 diabetes mellitus, brain atrophy, and cognitive decline

Moran, C., Beare, R., Wang, W., Callisaya, M., Srikanth, V., Weiner, M., Aisen, P., Petersen, R., Jack, C. R., Jagust, W., Trojanowki, J. Q., Toga, A. W., Beckett, L., Green, R. C., Saykin, A. J., Morris, J., Liu, E., Montine, T., Gamst, A., Thomas, R. G. & 234 others, Donohue, M., Walter, S., Gessert, D., Sather, T., Harvey, D., Kornak, J., Dale, A., Bernstein, M., Felmlee, J., Fox, N., Thompson, P., Schuff, N., Alexander, G., Decarli, C., Bandy, D., Koeppe, R. A., Foster, N., Reiman, E. M., Chen, K., Mathis, C., Cairns, N. J., Taylor-Reinwald, L., Trojanowki, J. Q., Shaw, L., Lee, V. M. Y., Korecka, M., Crawford, K., Neu, S., Foroud, T. M., Potkin, S., Shen, L., Kachaturian, Z., Frank, R., Snyder, P. J., Molchan, S., Kaye, J., Quinn, J., Lind, B., Dolen, S., Schneider, L. S., Pawluczyk, S., Spann, B. M., Brewer, J., Vanderswag, H., Heidebrink, J. L., Lord, J. L., Johnson, K., Doody, R. S., Villanueva-Meyer, J., Chowdhury, M., Stern, Y., Honig, L. S., Bell, K. L., Morris, J. C., Ances, B., Carroll, M., Leon, S., Mintun, M. A., Schneider, S., Marson, D., Griffith, R., Clark, D., Grossman, H., Mitsis, E., Romirowsky, A., Detoledo-Morrell, L., Shah, R. C., Duara, R., Varon, D., Roberts, P., Albert, M., Onyike, C., Kielb, S., Rusinek, H., De Leon, M. J., Glodzik, L., De Santi, S., Doraiswamy, P. M., Petrella, J. R., Coleman, R. E., Arnold, S. E., Karlawish, J. H., Wolk, D., Smith, C. D., Jicha, G., Hardy, P., Lopez, O. L., Oakley, M., Simpson, D. M., Porsteinsson, A. P., Goldstein, B. S., Martin, K., Makino, K. M., Ismail, M. S., Brand, C., Mulnard, R. A., Thai, G., McAdams-Ortiz, C., Womack, K., Mathews, D., Quiceno, M., Diaz-Arrastia, R., King, R., Weiner, M., Martin-Cook, K., Devous, M., Levey, A. I., Lah, J. J., Cellar, J. S., Burns, J. M., Anderson, H. S., Swerdlow, R. H., Apostolova, L., Lu, P. H., Bartzokis, G., Silverman, D. H. S., Graff-Radford, N. R., Parfitt, F., Johnson, H., Farlow, M. R., Hake, A. M., Matthews, B. R., Herring, S., Van Dyck, C. H., Carson, R. E., Macavoy, M. G., Chertkow, H., Bergman, H., Hosein, C., Black, S., Stefanovic, B., Caldwell, C., Robin Hsiung, G. Y., Feldman, H., Mudge, B., Assaly, M., Kertesz, A., Rogers, J., Trost, D., Bernick, C., Munic, D., Kerwin, D., Mesulam, M. M., Lipowski, K., Wu, C. K., Johnson, N., Sadowsky, C., Martinez, W., Villena, T., Turner, R. S., Johnson, K., Reynolds, B., Sperling, R. A., Johnson, K. A., Marshall, G., Frey, M., Yesavage, J., Taylor, J. L., Lane, B., Rosen, A., Tinklenberg, J., Sabbagh, M., Belden, C., Jacobson, S., Kowall, N., Killiany, R., Budson, A. E., Norbash, A., Johnson, P. L., Obisesan, T. O., Wolday, S., Bwayo, S. K., Lerner, A., Hudson, L., Ogrocki, P., Fletcher, E., Carmichael, O., Olichney, J., Kittur, S., Borrie, M., Bartha, D. R., Johnson, S., Asthana, S., Carlsson, C. M., Potkin, S. G., Preda, A., Nguyen, D., Tariot, P., Fleisher, A., Reeder, S., Bates, V., Capote, H., Rainka, M., Scharre, D. W., Kataki, M., Zimmerman, E. A., Celmins, D., Brown, A. D., Pearlson, G. D., Blank, K., Anderson, K., Santulli, R. B., Schwartz, E. S., Sink, K. M., Williamson, J. D., Garg, P., Watkins, F., Ott, B. R., Querfurth, H., Tremont, G., Salloway, S., Malloy, P., Correia, S., Rosen, H. J., Miller, B. L., Mintzer, J., Longmire, C. F., Spicer, K., Finger, E., Rachinsky, I., Drost, D., Pomara, N., Hernando, R., Sarrael, A., Schultz, S. K., Boles Ponto, L. L., Shim, H., Smith, K. E., Relkin, N., Chaing, G., Raudin, L., Smith, A., Fargher, K. & Raj, B. A., Feb 19 2019, In : Neurology. 92, 8, p. E823-E830

Research output: Contribution to journalArticle

7 Scopus citations
2020

Brain-wide structural connectivity alterations under the control of Alzheimer risk genes

Yan, J., Vinesh Raja, V., Huang, Z., Amico, E., Nho, K., Fang, S., Sporns, O., Wu, Y. C., Saykin, A., Goñi, J. & Shen, L., Jan 1 2020, In : International Journal of Computational Biology and Drug Design. 13, 1, p. 58-70 13 p.

Research output: Contribution to journalArticle

Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured SCCA approach

Du, L., Liu, K., Yao, X., Risacher, S. L., Han, J., Saykin, A. J., Guo, L. & Shen, L., Apr 2020, In : Medical Image Analysis. 61, 101656.

Research output: Contribution to journalArticle

2017

Preface micgen 2017

Dalca, A. V., Batmanghelich, N. K., Sabuncu, M. R. & Shen, L., Jan 1 2017, In : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10551 LNCS

Research output: Contribution to journalEditorial

2016

Machine learning in brain imaging genomics

Yan, J., Du, L., Yao, X. & Shen, L., Aug 9 2016, Machine Learning and Medical Imaging. Elsevier Inc., p. 411-434 24 p.

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations
2019

Interactive Machine Learning by Visualization: A Small Data Solution

Li, H., Fang, S., Mukhopadhyay, S., Saykin, A. & Shen, L., Jan 22 2019, Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018. Song, Y., Liu, B., Lee, K., Abe, N., Pu, C., Qiao, M., Ahmed, N., Kossmann, D., Saltz, J., Tang, J., He, J., Liu, H. & Hu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 3513-3521 9 p. 8621952. (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2017

Network-based genome wide study of hippocampal imaging phenotype in Alzheimer's Disease to identify functional interaction modules

Yao, X., Yan, J., Risacher, S., Moore, J., Saykin, A. & Shen, L., Jun 16 2017, 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 6170-6174 5 p. 7953342. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2019

Prioritizing Amyloid Imaging Biomarkers in Alzheimer’s Disease via Learning to Rank

for the ADNI, Jan 1 2019, Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy - 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Proceedings. Zhu, D., Yan, J., Huang, H., Shen, L., Thompson, P. M., Westin, C-F., Pennec, X., Joshi, S., Nielsen, M., Sommer, S., Fletcher, T. & Durrleman, S. (eds.). Springer, p. 139-148 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11846 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Rapid acceleration of the permutation test via transpositions

Chung, M. K., Xie, L., Huang, S. G., Wang, Y., Yan, J. & Shen, L., Jan 1 2019, Connectomics in NeuroImaging - 3rd International Workshop, CNI 2019, Held in Conjunction with MICCAI 2019, Proceedings. Schirmer, M. D., Chung, A. W., Venkataraman, A., Rekik, I. & Kim, M. (eds.). Springer, p. 42-53 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11848 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2016

A new statistical image analysis approach and its application to Hippocampal morphometry

ADNI, Jan 1 2016, Medical Imaging and Augmented Reality - 7th International Conference, MIAR 2016, Proceedings. Liao, H., Zheng, G., Lee, S-L., Cattin, P. & Jannin, P. (eds.). Springer Verlag, p. 302-310 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9805 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations
2017

Identifying associations between brain imaging phenotypes and genetic factors via a novel structured SCCA approach

Du, L., Zhang, T., Liu, K., Yan, J., Yao, X., Risacher, S. L., Saykin, A., Han, J., Guo, L. & Shen, L., 2017, Information Processing in Medical Imaging - 25th International Conference, IPMI 2017, Proceedings. Springer Verlag, Vol. 10265 LNCS. p. 543-555 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10265 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Transcriptome-guided imaging genetic analysis via a novel sparse CCA algorithm

Alzheimer’s Disease Neuroimaging Initiative, 2017, Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - 1st International Workshop, GRAIL 2017 6th International Workshop, MFCA 2017 and 3rd International Workshop, MICGen 2017 Held in Conjunction with MICCAI 2017, Proceedings. Springer Verlag, Vol. 10551 LNCS. p. 220-229 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10551 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2016

Building a surface atlas of hippocampal subfields from high resolution T2-weighted MRI scans using landmark-free surface registration

Cong, S., Rizkalla, M., Salama, P., Risacher, S. L., West, J. D., Wu, Y. C., Apostolova, L., Tallman, E., Saykin, A. J. & Shen, L., Jul 2 2016, 2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016. Institute of Electrical and Electronics Engineers Inc., 7870109. (Midwest Symposium on Circuits and Systems; vol. 0).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations
2019

Targeted genetic analysis of cerebral blood flow imaging phenotypes implicates the INPP5D gene

Alzheimer's Disease Neuroimaging Initiative, Sep 2019, In : Neurobiology of Aging. 81, p. 213-221 9 p.

Research output: Contribution to journalArticle

1 Scopus citations
2018

Quantitative trait loci identification for brain endophenotypes via new additive model with random networks

Wang, X., Chen, H., Yan, J., Nho, K., Risacher, S. L., Saykin, A. J., Shen, L. & Huang, H., Sep 1 2018, In : Bioinformatics. 34, 17, p. i866-i874

Research output: Contribution to journalArticle

1 Scopus citations

Predicting progressions of cognitive outcomes via high-order multi-modal multi-task feature learning

Lu, L., Wang, H., Yao, X., Risacher, S., Saykin, A. & Shen, L., May 23 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. IEEE Computer Society, Vol. 2018-April. p. 545-548 4 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations
2017

Mapping longitudinal scientific progress, collaboration and impact of the Alzheimer’s disease neuroimaging initiative

Alzheimer’s Disease Neuroimaging Initiative, Nov 1 2017, In : PLoS One. 12, 11, e0186095.

Research output: Contribution to journalArticle

5 Scopus citations
2019

Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: A longitudinal study of the ADNI cohort

Du, L., Liu, K., Zhu, L., Yao, X., Risacher, S. L., Guo, L., Saykin, A. J. & Shen, L., Jul 15 2019, In : Bioinformatics. 35, 14, p. i474-i483 btz320.

Research output: Contribution to journalArticle

Open Access
3 Scopus citations