Becerra, Mauricio

Identification of genetic risk factors in the Chinese population implicates a role of immune system in Alzheimer’s disease pathogenesis

Zhou, X., Chen, Y., Mok, K. Y., Zhao, Q., Chen, K., Chen, Y., Hardy, J., Li, Y., Fu, A. K. Y., Guo, Q., et al. (2018) · Proceedings of the National Academy of Sciences

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 96

Staging tau pathology with tau PET in Alzheimer’s disease: a longitudinal study

Chen, S.-D., Lu, J.-Y., Li, H.-Q., Yang, Y.-X., Jiang, J.-H., Cui, M., Zuo, C.-T., Tan, L., Dong, Q., Yu, J.-T., et al. (2021) · Translational Psychiatry

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

Cited by 71

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

Cited by 18

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

Cited by 18

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

Cited by 15