| Autor: |
Etienne Maheux, Igor Koval, Juliette Ortholand, Colin Birkenbihl, Damiano Archetti, Vincent Bouteloup, Stéphane Epelbaum, Carole Dufouil, Martin Hofmann-Apitius, Stanley Durrleman |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Nature Communications, Vol 14, Iss 1, Pp 1-15 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2041-1723 |
| DOI: |
10.1038/s41467-022-35712-5 |
| Popis: |
Accurate prediction of disease progression in Alzheimer’s disease (AD) is necessary for optimal recruitment of patients to clinical trials. Here, the authors present AD Course Map, a statistical model which helps to predict disease progression in participants, thus decreasing the required sample size for a hypothetical trial. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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