A robust and interpretable machine learning approach using multimodal biological data to predict future pathological tau accumulation
| Autor: | Joseph Giorgio, William J. Jagust, Suzanne Baker, Susan M. Landau, Peter Tino, Zoe Kourtzi, Alzheimer’s Disease Neuroimaging Initiative |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Nature Communications, Vol 13, Iss 1, Pp 1-14 (2022) |
| Druh dokumentu: | article |
| ISSN: | 2041-1723 19544693 |
| DOI: | 10.1038/s41467-022-28795-7 |
| Popis: | The authors present a machine learning approach that combines baseline multimodal data to accurately predict individualised trajectories of future pathological tau accumulation at asymptomatic and mildly impaired stages of Alzheimer’s disease. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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