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Machine learning for comprehensive forecasting of Alzheimer’s Disease progression
Most approaches to machine learning from electronic health data can only predict a single endpoint. The ability to simultaneously simulate dozens of patient characteristics is a crucial step towards personalized medicine for Alzheimer’s Disease. Here, we use an unsupervised machine learning model ca...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754403/ https://www.ncbi.nlm.nih.gov/pubmed/31541187 http://dx.doi.org/10.1038/s41598-019-49656-2 |