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Machine learning approaches to predicting amyloid status using data from an online research and recruitment registry: The Brain Health Registry.
Albright, Jack; Ashford, Miriam T; Jin, Chengshi; Neuhaus, John; Rabinovici, Gil D; Truran, Diana; Maruff, Paul; Mackin, R Scott; Nosheny, Rachel L; Weiner, Michael W.
Affiliation
  • Albright J; The Nueva School San Mateo California USA.
  • Ashford MT; Department of Veterans Affairs Medical Center Northern California Institute for Research and Education (NCIRE) San Francisco California USA.
  • Jin C; Department of Veterans Affairs Medical Center Center for Imaging and Neurodegenerative Diseases San Francisco California USA.
  • Neuhaus J; University of California San Francisco Department of Epidemiology and Biostatistics San Francisco California USA.
  • Rabinovici GD; University of California San Francisco Department of Epidemiology and Biostatistics San Francisco California USA.
  • Truran D; Department of Radiology and Biomedical Imaging University of California San Francisco California USA.
  • Maruff P; Department of Neurology University of California San Francisco San Francisco California USA.
  • Mackin RS; Department of Veterans Affairs Medical Center Northern California Institute for Research and Education (NCIRE) San Francisco California USA.
  • Nosheny RL; Department of Veterans Affairs Medical Center Center for Imaging and Neurodegenerative Diseases San Francisco California USA.
  • Weiner MW; Cogstate, Ltd. Melbourne VIC Australia.
Alzheimers Dement (Amst) ; 13(1): e12207, 2021.
Article in En | MEDLINE | ID: mdl-34136635
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Alzheimers Dement (Amst) Year: 2021 Document type: Article Country of publication: Estados Unidos
Fulltext
Add to My VHL
Print
XML
PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Alzheimers Dement (Amst) Year: 2021 Document type: Article Country of publication: Estados Unidos