ArticleFrontiers in psychiatry2021
Improving Individual Brain Age Prediction Using an Ensemble Deep Learning Framework.
Article in Frontiers in psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Age and sex estimation using post-mortem CT scout view.International journal of legal medicine · 2026Article
- Association of imaging-defined brain age with disease severity and adverse outcomes in CADASIL.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Brain age prediction in generalized anxiety disorder using a convolutional neural network.Translational psychiatry · 2026Article
- Integration of Genetic Information to Improve Brain Age Gap Estimation Models in the UK Biobank.Human brain mapping · 2025Article
- Brain Age Prediction: Deep Models Need a Hand to Generalize.Human brain mapping · 2025Article
- Do Transformers and CNNs Learn Different Concepts of Brain Age?Human brain mapping · 2025Article
- Characterizing multivariate regional hubs for schizophrenia classification, sex differences, and brain age estimation using explainable AI.medRxiv : the preprint server for health sciences · 2025Article
- Disparities in accelerated brain aging in recent-onset and chronic schizophrenia.Psychological medicine · 2025Article
- Machine Learning and Deep Learning Approaches in Lifespan Brain Age Prediction: A Comprehensive Review.Tomography (Ann Arbor, Mich.) · 2024Review
- Deep Learning-based Brain Age Prediction in Patients With Schizophrenia Spectrum Disorders.Schizophrenia bulletin · 2024Article
- A ResNet mini architecture for brain age prediction.Scientific reports · 2024Article
- Dissecting unique and common variance across body and brain health indicators using age prediction.Human brain mapping · 2024Article
- White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.Molecular psychiatry · 2024Article
- Acceleration of brain aging after small-volume infarcts.Frontiers in aging neuroscience · 2024Article
- Brain age prediction using combined deep convolutional neural network and multi-layer perceptron algorithms.Scientific reports · 2023Article
- Extensive T1-weighted MRI Preprocessing Improves Generalizability of Deep Brain Age Prediction Models.bioRxiv : the preprint server for biology · 2023Article
- An Ensemble of Deep Learning Object Detection Models for Anatomical and Pathological Regions in Brain MRI.Diagnostics (Basel, Switzerland) · 2023Article
- Benchmarking the generalizability of brain age models: Challenges posed by scanner variance and prediction bias.Human brain mapping · 2023Article
- A Deep Learning Approach to Predict Chronological Age.Healthcare (Basel, Switzerland) · 2023Article
- Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain age is an imaging-based biomarker with excellent feasibility for characterizing individual brain health and may serve as a single quantitative index for clinical and domain-specific usage. Brain age has been successfully estimated using extensive neuroimaging data from healthy participants with various feature extraction and conventional machine learning (ML) approaches. Recently, several end-to-end deep learning (DL) analytical frameworks have been proposed as alternative approaches to predict individual brain age with higher accuracy. However, the optimal approach to select and assemble appropriate input feature sets for DL analytical frameworks remains to be determined. In the Predictive Analytics Competition 2019, we proposed a hierarchical analytical framework which first used ML algorithms to investigate the potential contribution of different input features for predicting individual brain age. The obtained information then served as
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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.