Shen, Li

Divergent Cortical Tau Positron Emission Tomography Patterns Among Patients With Preclinical Alzheimer Disease

Young, C. B., Winer, J. R., Younes, K., Cody, K. A., Betthauser, T. J., Johnson, S. C., Schultz, A., Sperling, R. A., Greicius, M. D., Cobos, I., et al. (2022) · JAMA Neurology

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AD-BERT: Using pre-trained language model to predict the progression from mild cognitive impairment to Alzheimer's disease

Mao, C., Xu, J., Rasmussen, L., Li, Y., Adekkanattu, P., Pacheco, J., Bonakdarpour, B., Vassar, R., Shen, L., Jiang, G., et al. (2023) · Journal of Biomedical Informatics

Machine Learning in HealthcareDementia and Cognitive Impairment Research

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White matter abnormalities and cognition in aging and Alzheimer disease

Peter, C., Sathe, A., Shashikumar, N., Pechman, K. R., Workmeister, A. W., Jackson, T. B., Huo, Y., Mukherjee, S., Mez, J., Dumitrescu, L. C., et al. (2025) · JAMA Neurology

Dementia and Cognitive Impairment ResearchAdvanced Neuroimaging Techniques and Applications

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KL-VS heterozygosity is associated with lower amyloid-dependent tau accumulation and memory impairment in Alzheimer’s disease

Neitzel, J., Franzmeier, N., Rubinski, A., Dichgans, M., Brendel, M., (ADNI), A. D. N. I., Weiner, M., Aisen, P., Petersen, R., Jack, C. R., et al. (2021) · Nature Communications

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

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Multimodal Hippocampal Subfield Grading For Alzheimer’s Disease Classification

Hett, K., Ta, V.-T., Catheline, G., Tourdias, T., Manjón, J. V., Coupé, P., Initiative, A. D. N., Weiner, M. W., Aisen, P., Petersen, R., et al. (2019) · Scientific Reports

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

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

Yao, X., Risacher, S. L., Nho, K., Saykin, A. J., Wang, Z., & Shen, L. (2019) · Neurobiology of Aging

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

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Genetic studies of plasma analytes identify novel potential biomarkers for several complex traits

Deming, Y., Xia, J., Cai, Y., Lord, J., Del-Aguila, J. L., Fernandez, M. V., Carrell, D., Black, K., Budde, J., Ma, S., et al. (2016) · Scientific Reports

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

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Towards cascading genetic risk in Alzheimer’s disease

Altmann, A., Aksman, L. M., Oxtoby, N. P., Young, A. L., ADNI, Weiner, M., Aisen, P., Petersen, R., Weiner, M., Aisen, P., et al. (2024) · Brain

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

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Deep learning to quantify the pace of brain aging in relation to neurocognitive changes

Yin, C., Imms, P., Chowdhury, N. F., Chaudhari, N. N., Ping, H., Wang, H., Bogdan, P., Irimia, A., Initiative, T. A. D. N., Weiner, M., et al. (2025) · Proceedings of the National Academy of Sciences

Dementia and Cognitive Impairment ResearchAdvanced MRI Techniques and Applications

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Identifying progression-specific Alzheimer’s subtypes using multimodal transformer

Machado Reyes, D., Chao, H., Hahn, J., Shen, L., Yan, P., & Initiative, F. T. A. D. N. (2024) · Journal of Personalized Medicine

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

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Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural Bayesian factor analysis

Bao, J., Chang, C., Zhang, Q., Saykin, A. J., Shen, L., Long, Q., & Initiative, F. T. A. D. N. (2023) · Briefings in Bioinformatics

Bioinformatics and Genomic NetworksDementia and Cognitive Impairment Research

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Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

Jo, T., Kim, J., Bice, P., Huynh, K., Wang, T., Arnold, M., Meikle, P. J., Giles, C., Kaddurah-Daouk, R., Saykin, A. J., et al. (2023) · eBioMedicine

Dementia and Cognitive Impairment ResearchMetabolomics and Mass Spectrometry Studies

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications.

Yang, S., Pham, N. T., Li, Z., Baik, J. Y., Lee, J., Zhai, T., Yu, W., Hou, B., Shang, T., He, W., et al. (2025) · arXiv

RNA and protein synthesis mechanismsRNA modifications and cancer

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EG-BINN: Parameter-Efficient Ensembling of Gated Biologically Informed Neural Networks for Epigenetic Age Estimation

Edwards, T., Long, Q., & Shen, L. (2026) · bioRxiv (Cold Spring Harbor Laboratory)

Epigenetics and DNA MethylationGenetics, Aging, and Longevity in Model Organisms

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