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Identifying healthy individuals with Alzheimer's disease neuroimaging phenotypes in the UK Biobank.
Azevedo, Tiago; Bethlehem, Richard A I; Whiteside, David J; Swaddiwudhipong, Nol; Rowe, James B; Lió, Pietro; Rittman, Timothy.
Afiliación
  • Azevedo T; Department of Computer Science and Technology, University of Cambridge, Cambridge, UK.
  • Bethlehem RAI; Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
  • Whiteside DJ; Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
  • Swaddiwudhipong N; Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK.
  • Rowe JB; Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK.
  • Lió P; Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK.
  • Rittman T; Department of Computer Science and Technology, University of Cambridge, Cambridge, UK.
Commun Med (Lond) ; 3(1): 100, 2023 Jul 20.
Article en En | MEDLINE | ID: mdl-37474615
Spotting people with dementia early is challenging, but important to identify people for trials of treatment and prevention. We used brain scans of people with Alzheimer's disease, the commonest type of dementia, and applied an artificial intelligence method to spot people with Alzheimer's disease. We used this to find people in the Healthy UK Biobank study who might have early Alzheimer's disease. The people we found had subtle changes in their memory and thinking to suggest they may have early disease, and we also found they had high blood pressure and smoked for longer. We have demonstrated an approach that could be used to select people at high risk of future dementia for clinical trials.

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Commun Med (Lond) Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Commun Med (Lond) Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido