Li Shen

  • 7148 Citations
  • 45 h-Index
19972020
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  • 3 Similar Profiles
Alzheimer Disease Medicine & Life Sciences
Neuroimaging Medicine & Life Sciences
Brain Engineering & Materials Science
Imaging techniques Engineering & Materials Science
Genome-Wide Association Study Medicine & Life Sciences
Single Nucleotide Polymorphism Medicine & Life Sciences
Imaging Mathematics
Alzheimer's Disease Mathematics

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NIH Grants 2008 2020

Neuroimaging
Bioinformatics
Brain
Genes
Imaging techniques
Bioinformatics
Brain
Imaging techniques
Nucleotides
Polymorphism
Harmonic functions
Brain
Imaging techniques
Neuroimaging
Volume measurement

Publications 1997 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
Hippocampus
Alzheimer Disease
Neural Networks (Computer)
Magnetic Resonance Imaging
ROC Curve

Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease

for the Alzheimer's Disease Neuroimaging Initiative, Feb 2020, In : Medical Image Analysis. 60, 101625.

Research output: Contribution to journalArticle

Neuroimaging
Feature extraction
Alzheimer Disease
Magnetic resonance imaging
Positron emission tomography

Predicting Longitudinal Outcomes of Alzheimer's Disease via a Tensor-Based Joint Classification and Regression Model

Alzheimer’s Disease Neuroimaging Initiative, Jan 1 2020, In : Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 25, p. 7-18 12 p.

Research output: Contribution to journalArticle

Tensors
Alzheimer Disease
Joints
Learning systems
Neuroimaging

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

Multi-task Learning
Brain
Imaging
Imaging techniques
Modality

A Unified Model for Robust Differential Expression Analysis of RNA-Seq Data

Liu, K., Shen, L. & Jian, H., 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. 437-442 6 p. 8621331. (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

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

RNA
Genes
Linear Models
Gene Expression
Gene expression