Albert, Marilyn

Genetic and clinical correlates of AI-based brain aging patterns in cognitively unimpaired individuals

Skampardoni, I., Nasrallah, I. M., Abdulkadir, A., Wen, J., Melhem, R., Mamourian, E., Erus, G., Doshi, J., Singh, A., Yang, Z., et al. (2024) · JAMA Psychiatry

Dementia and Cognitive Impairment ResearchFunctional Brain Connectivity Studies

Cited by 28

Surface-based analysis on shape and fractional anisotropy of white matter tracts in Alzheimer’s disease

Qiu, A., Oishi, K., Miller, M. I., Lyketsos, C. G., Mori, S., & Albert, M. (2010) · PLoS ONE

Advanced Neuroimaging Techniques and ApplicationsDementia and Cognitive Impairment Research

Cited by 26

Regional White Matter Hyperintensities and Alzheimer’s Disease Biomarkers Among Older Adults with Normal Cognition and Mild Cognitive Impairment

Newton, P., the BIOCARD Research Team, Tchounguen, J., Pettigrew, C., Lim, C., Lin, Z., Lu, H., Moghekar, A., Albert, M., & Soldan, A. (2023) · Journal of Alzheimer's Disease

Dementia and Cognitive Impairment ResearchCerebrovascular and genetic disorders

Cited by 23

Atlas-Based Diffusion Tensor Imaging Correlates of Executive Function

Nowrangi, M. A., Okonkwo, O., Lyketsos, C., Oishi, K., Mori, S., Albert, M., & Mielke, M. M. (2015) · Journal of Alzheimer's Disease

Advanced Neuroimaging Techniques and ApplicationsDementia and Cognitive Impairment Research

Cited by 19

Amyloid-β predominant Alzheimer’s disease neuropathologic change

Kovacs, G. G., Katsumata, Y., Wu, X., Aung, K. Z., Fardo, D. W., Forrest, S. L., Alzheimer's Disease Genetics Consortium, Bowen, J. D., Crane, P. K., Jarvik, G. P., et al. (2025) · Brain

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 19

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

In vivo cortical diffusion imaging relates to Alzheimer's disease neuropathology

Torso, M., Ridgway, G. R., Valotti, M., Hardingham, I., Chance, S. A., for the National Alzheimer’s Coordinating Center, Brewer, J., Lopez, O., Hyman, B., Grabowski, T., et al. (2023) · Alzheimer's Research & Therapy

Dementia and Cognitive Impairment ResearchAdvanced Neuroimaging Techniques and Applications

Cited by 16

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