ArticleBrain communications2022
Disentangling Alzheimer's disease neurodegeneration from typical brain ageing using machine learning.
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Article in Brain communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20citing papers in PubMed
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Who cites it
20 citing papers in PubMed, 28 citations in OpenAlex.
- Comparative Study of Anatomical and Learned Features in AI Models for Structural Brain MRI.Research square · 2026Article
- Elucidating the neuropathological and molecular heterogeneity of amyloid beta and tau in Alzheimer's disease through machine learning and transcriptomic integration.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Mapping Neuroanatomical Heterogeneity of Brain Aging Within a Clinically Defined Aging Reference Cohort.Bioengineering (Basel, Switzerland) · 2026Article
- Evaluation of an in vivo biomarker of arteriolosclerosis (ARTS) and its associations with cognition and multimodal ATN(V) biomarkers in a cardiometabolic-risk enriched community cohort.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Coupled cross-sectional and longitudinal non-negative matrix factorization reveals dominant brain aging trajectories in 48,949 individuals.Nature communications · 2026Article
- Alzheimer's Disease Brain Phenotypes are Age-dependent.bioRxiv : the preprint server for biology · 2026Article
- Evaluation of an in vivo biomarker of arteriolosclerosis (ARTS) and its associations with cognition and multimodal ATN(V) biomarkers in a cardiometabolic-risk enriched community cohort.medRxiv : the preprint server for health sciences · 2025Article
- Aging as an active player in Alzheimer's disease classification: Insights from feature selection in BrainAge models.NeuroImage · 2025Article
- Aging as an active player in Alzheimer's Disease Classification: Insights from feature selection in BrainAge Models.medRxiv : the preprint server for health sciences · 2025Article
- Radiomic and proteomic signatures of body mass index on brain ageing and Alzheimer's-like patterns of brain atrophy.EBioMedicine · 2025Article
- Preclinical Alzheimer's and vascular biomarkers alter brain aging in cognitively normal adults: a MRI-based study.Frontiers in aging neuroscience · 2025Article
- Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap.Neurology · 2024Article
- Tau-neurodegeneration mismatch reveals vulnerability and resilience to comorbidities in Alzheimer's continuum.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Differential diagnosis of frontotemporal dementia subtypes with explainable deep learning on structural MRI.Frontiers in neuroscience · 2024Article
- Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach.Journal of Alzheimer's disease : JAD · 2024Article
- Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population.JAMA psychiatry · 2023Article
- Observational
- A deep learning model for brain age prediction using minimally preprocessed T1w images as input.Frontiers in aging neuroscience · 2023Article
- Brain age prediction using the graph neural network based on resting-state functional MRI in Alzheimer's disease.Frontiers in neuroscience · 2023Article
- NODDI in gray matter is a sensitive marker of aging and early AD changes.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
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Authors and funding
22 authors at 7 institutions in 1 country.
Gyujoon HwangCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.ORCID https://orcid.org/0000-0002-9497-2999
Ahmed AbdulkadirCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
Guray ErusCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
Mohamad HabesGlenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
Raymond PomponioCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
Haochang ShouCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
Jimit DoshiCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
Elizabeth MamourianCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
Tanweer RashidCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
Murat BilgelLaboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA.ORCID https://orcid.org/0000-0001-5042-7422
Yong FanCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
Aristeidis SotirasCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
Dhivya SrinivasanCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
John C MorrisDepartment of Neurology, Washington University in St Louis, St Louis, MO, USA.ORCID https://orcid.org/0000-0003-2967-9662
Marilyn S AlbertDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Nick R BryanDepartment of Diagnostic Medicine, University of Texas, Austin, TX, USA.
Susan M ResnickLaboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA.
Ilya M NasrallahCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
Christos DavatzikosCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.ORCID https://orcid.org/0000-0002-1025-8561
David A WolkCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.
from the iSTAGING consortium
ADNI
University of Pennsylvania · USNational Institute on Aging · USPenn Center for AIDS Research · USWashington University in St. Louis · USJohns Hopkins University · USThe University of Texas at Austin · USThe University of Texas Health Science Center at San Antonio · US
Funding
Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0MProject 2 MeasurementU19AG033655 · NIA · JOHNS HOPKINS UNIVERSITY · PI Abhay Moghekar · 2014 to 2026
$51.5MThe natural history of AB accumulation in preclinical ADP01AG026276 · NIA · WASHINGTON UNIVERSITY · PI MORRIS, JOHN · 2005 to 2025
$49.5MUPenn ADCC Biomarker CoreP30AG010124 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DETRE, JOHN A · 1991 to 2020
$35.1MResearch Education ComponentP30AG066507 · NIA · JOHNS HOPKINS UNIVERSITY · PI MARILYN S. ALBERT · 2020 to 2026
$29.3MResearch Education ComponentP30AG072979 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DAVID A WOLK · 2021 to 2026
$24.8MAmyloid Imaging, VMCI, and Analysis for ADNIRC2AG036535 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI WEINER, MICHAEL W · 2009 to 2010
$23.8MUltrascale Machine Learning to Empower Discovery in Alzheimers Disease BiobanksU01AG068057 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Christos Davatzikos, Heng Huang · 2020 to 2026
$20.7MBiomarkers of Cognitive Decline among Normal Individuals: The BIOCARD cohortU01AG033655 · NIA · JOHNS HOPKINS UNIVERSITY · PI ALBERT, MARILYN S. · 2009 to 2013
$11.2MPreclinical AD ConsortiumRF1AG059869 · NIA · JOHNS HOPKINS UNIVERSITY · PI ALBERT, MARILYN S. · 2018 to 2018
$7.7MMachine Learning and Large-scale Imaging analytics for dimensional representations of brain trajectories in aging and preclinical Alzheimer's Disease: The brain aging chart and the iSTAGING consortiumRF1AG054409 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DAVATZIKOS, CHRISTOS · 2017 to 2023
$6.3MMachine Learning and Large-scale Imaging analytics for dimensional representations of brain trajectories in aging and preclinical Alzheimer's Disease: The brain aging chart and the iSTAGING consortiumR01AG054409 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Christos Davatzikos · 2025 to 2026
$1.4MNIA NIH HHS P01 AG026276NIA NIH HHS P30 AG010124NIA NIH HHS P30 AG066507NIA NIH HHS P30 AG072979NIA NIH HHS R01 AG054409NIA NIH HHS RC2 AG036535NIA NIH HHS RF1 AG054409NIA NIH HHS RF1 AG059869NIA NIH HHS U01 AG024904NIA NIH HHS U01 AG033655NIA NIH HHS U01 AG068057NIA NIH HHS U19 AG033655
Abstract
Neuroimaging biomarkers that distinguish between changes due to typical brain ageing and Alzheimer's disease are valuable for determining how much each contributes to cognitive decline. Supervised machine learning models can derive multivariate patterns of brain change related to the two processes, including the Spatial Patterns of Atrophy for Recognition of Alzheimer's Disease (SPARE-AD) and of Brain Aging (SPARE-BA) scores investigated herein. However, the substantial overlap between brain regions affected in the two processes confounds measuring them independently. We present a methodology, and associated results, towards disentangling the two. T
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Alzheimer’s diseaseamyloidbrain ageingmachine learningMRI biomarker
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.