ArticleProceedings of the National Academy of Sciences of the United States of America2025
Deep learning to quantify the pace of brain aging in relation to neurocognitive changes.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Deep survival modeling to predict future cognitive impairment in unimpaired adults.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026Article
- Women's reproductive factors predict local brain aging profiles mapped using deep neural networks.GeroScience · 2026Article
- Deep Learning-Based Structural Brain Age Estimation in Bipolar Disorder and Schizophrenia: A Single-Site Pilot Study.Human brain mapping · 2026Article
- Enhancing brain age estimation with structural MRI and synthesized cerebral blood volume maps.Brain communications · 2026Article
- Prediction of brain age using structural magnetic resonance imaging: a comparison of clinical utility of publicly available software packages.EBioMedicine · 2026Article
- Multimodal neuroimaging and AI integration in cognitive disorders: advances, challenges, and future directions for precision medicine.Psychoradiology · 2026Review
- Brain age gap as predictor of disease progression in Parkinson's disease.NPJ Parkinson's disease · 2025Article
- GrimAge and GrimAge2 Age Acceleration effectively predict mortality risk: a retrospective cohort study.Epigenetics · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Brain age (BA), distinct from chronological age (CA), can be estimated from MRIs to evaluate neuroanatomic aging in cognitively normal (CN) individuals. BA, however, is a cross-sectional measure that summarizes cumulative neuroanatomic aging since birth. Thus, it conveys poorly recent or contemporaneous aging trends, which can be better quantified by the (temporal) pace
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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.