A deep learning model for brain age prediction using minimally preprocessed T1w images as input.

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第一作者： Caroline,Dartora

第一单位： Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.

作者： Caroline,Dartora ^[1] ; Anna,Marseglia ^[1] ; Gustav,Mårtensson ^[1] ; Gull,Rukh ^[2] ; Junhua,Dang ^[2] ; J-Sebastian,Muehlboeck ^[1] ; Lars-Olof,Wahlund ^[1] ; Rodrigo,Moreno ^[3] ; José,Barroso ^[4] ; Daniel,Ferreira ^[1] ; Helgi B,Schiöth ^[4] ; Eric,Westman ^[2] ; Alzheimer’s Disease Neuroimaging Initiative ^[1] ; Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing ^[5] ; Japanese Alzheimer’s Disease Neuroimaging Initiative ; AddNeuroMed Consortium

作者单位： Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden. ^[1] Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, Sweden. ^[2] Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Stockholm, Sweden. ^[3] Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas, España. ^[4] Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom. ^[5]

关键词 CNN UK Biobank ageing prediction brain age neurodegeneration normal ageing

DOI 10.3389/fnagi.2023.1303036

PMID 38259636

发布时间 2024-02-10

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Frontiers in aging neuroscience

2023年15卷

1303036页

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A deep learning model for brain age prediction using minimally preprocessed T1w images as input.

Frontiers in aging neuroscience

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Frontiers in aging neuroscience

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A deep learning model for brain age prediction using minimally preprocessed T1w images as input.

Frontiers in aging neuroscience

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Frontiers in aging neuroscience

相关期刊

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