ReviewJournal of personalized medicine2022
Neuroimaging-Based Brain Age Estimation: A Promising Personalized Biomarker in Neuropsychiatry.
Review in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Neuroanatomical signatures of chronotype in young adults.Brain imaging and behavior · 2026Article
- Metabolomic signatures reveal an association between healthy dietary patterns and brain aging.The journal of nutrition, health & aging · 2026Article
- Epigenetic aging and rejuvenation of the brain: drivers, consequences, and interventions.BMB reports · 2026Review
- Brain Age as a Biomarker in Alzheimer's Disease: Narrative Perspectives on Imaging, Biomarkers, Machine Learning, and Intervention Potential.Brain sciences · 2025Review
- Neuroanatomical features reveal accelerated brain age in alcohol use disorder.bioRxiv : the preprint server for biology · 2025Article
- Integration of Genetic Information to Improve Brain Age Gap Estimation Models in the UK Biobank.Human brain mapping · 2025Article
- The effect of lesion filling on brain age estimation in multiple sclerosis.BMC medical imaging · 2025Article
- Association of Psychological Resilience With Decelerated Brain Aging in Cognitively Healthy World Trade Center Responders.Biological psychiatry global open science · 2025Article
- Brain Aging in Patients With Cardiovascular Disease From the UK Biobank.Human brain mapping · 2025Article
- Volumetric Changes in Cerebellar Transverse Zones: Age and Sex Effects in Health and Neurological Disorders.Human brain mapping · 2025Article
- Neuropsychiatric symptoms and neuroimaging-based brain age in mild cognitive impairment and early dementia: A multicenter study.Psychiatry and clinical neurosciences · 2025Article
- Unravelling pathological ageing with brain age gap estimation in Alzheimer's disease, diabetes and schizophrenia.Brain communications · 2025Article
- Article
- Seeking the neural basis of neuropsychiatric symptoms in dementia: neuroimaging findings and controversies.Frontiers in aging neuroscience · 2025Review
- Low-Rank Tensor Fusion for Enhanced Deep Learning-Based Multimodal Brain Age Estimation.Brain sciences · 2024Article
- Exploring the link between tooth loss, cognitive function, and brain wellness in the context of healthy aging.Journal of periodontal research · 2024Article
- White matter brain-age in diverse forms of epilepsy and interictal psychosis.Scientific reports · 2024Article
- MRI-informed machine learning-driven brain age models for classifying mild cognitive impairment converters.Journal of central nervous system disease · 2024Article
- Cerebrovascular lesion loads and accelerated brain aging: insights into the cognitive spectrum.Frontiers in dementia · 2024Article
- Brain Age Prediction Using 2D Projections Based on Higher-Order Statistical Moments and Eigenslices from 3D Magnetic Resonance Imaging Volumes.Journal of imaging · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
It is now possible to estimate an individual's brain age via brain scans and machine-learning models. This validated technique has opened up new avenues for addressing clinical questions in neurology, and, in this review, we summarize the many clinical applications of brain-age estimation in neuropsychiatry and general populations. We first provide an introduction to typical neuroimaging modalities, feature extraction methods, and machine-learning models that have been used to develop a brain-age estimation framework. We then focus on the significant findings of the brain-age estimation technique in the field of neuropsychiatry as well as the usefulness of the technique for addressing clinical questions in neuropsychiatry. These applications may contribute to more timely and targeted neuropsychiatric therapies. Last, we discuss the practical problems and challenges described in the literature and suggest some future research directions.
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Registered trials
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.