Sadowsky, Carl

Longitudinal measurement and hierarchical classification framework for the prediction of Alzheimer’s disease

Huang, M., Yang, W., Feng, Q., Chen, W., Initiative, T. A. D. N., Weiner, M. W., Aisen, P., Petersen, R., Jack, C. R., Jagust, W., et al. (2017) · Scientific Reports

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

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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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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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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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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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