Machine learning prediction of tau‐PET in Alzheimer's disease using plasma, MRI, and clinical data

Accessible variables showed potential in estimating tau tangle load and distribution. Plasma phosphorylated tau-217 (p-tau217) and magnetic resonance imaging (MRI) were the best predictors of different tau-PET (positron emission tomography) composites. Machine learning models demonstrated high generalizability across AD cohorts.

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Publication Details

Journal
Alzheimer s & Dementia
Published
2025-02-01
DOI
https://doi.org/10.1002/alz.14600
Citations
20
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
29.42

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article

Machine learning prediction of tau‐PET in Alzheimer's disease using plasma, MRI, and clinical data

Nicholas James Ashton, Alexa Pichet Binette, Richard A. I. Bethlehem, Renaud La Joie et al.
20 citations
Alzheimer s & Dementia
Dementia and Cognitive Impairment Research
29.42
article

Machine learning prediction of tau‐PET in Alzheimer's disease using plasma, MRI, and clinical data

Nicholas James Ashton, Alexa Pichet Binette, Richard A. I. Bethlehem, Renaud La Joie, Sebastian Palmqvist, Rik Ossenkoppele, Erik Stomrud, Olof T. Strandberg, Ruben Smith, Niklas Mattsson, Oskar Hansson, Gil Dan Rabinovici, Jakob Seidlitz, Kalle Åström, Shorena Janelidze, Jacob W. Vogel, Ida Arvidsson, Linda Karlsson, Henrik Zetterberg, Kaj Blennow
article en
20 citations

Abstract

Accessible variables showed potential in estimating tau tangle load and distribution. Plasma phosphorylated tau-217 (p-tau217) and magnetic resonance imaging (MRI) were the best predictors of different tau-PET (positron emission tomography) composites. Machine learning models demonstrated high generalizability across AD cohorts.

Alzheimer s & DementiaVol. 21(2)
University of Science and Technology of China (CN), Statistics Sweden (SE), Children's Hospital of Philadelphia (US), University of California, San Francisco (US), King's College London (GB), Lund University (SE), University of Cambridge (GB), Science for Life Laboratory (SE), Hong Kong Science and Technology Parks Corporation (HK), Sahlgrenska University Hospital (SE), University of California System (US), Sorbonne Université (FR), Amsterdam Neuroscience (NL), Pitié-Salpêtrière Hospital (FR), Translational Therapeutics (United States) (US), UK Dementia Research Institute (GB), Skåne University Hospital (SE), National Hospital for Neurology and Neurosurgery (GB), Lifespan (US), Amsterdam University Medical Centers (NL), Institut du Cerveau (FR), University College London (GB), University of Pennsylvania (US), University of Gothenburg (SE)
Alzheimer's Association, EU Joint Programme – Neurodegenerative Disease Research, Hjärnfonden, Knut och Alice Wallenbergs Stiftelse, Vetenskapsrådet, Alzheimerfonden, Science for Life Laboratory, Skånes universitetssjukhus, Parkinsonfonden, Horizon 2020 Framework Programme, National Institute on Aging, H2020 European Research Council
Openalex Percentile: Top 0%
Dementia and Cognitive Impairment Research
29.42
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