ArticleNeurobiology of aging2020
Estimating brain age based on a uniform healthy population with deep learning and structural magnetic resonance imaging.
Article in Neurobiology of aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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36 citing papers in PubMed, 100 citations in OpenAlex.
- Generalizable and explainable deep learning for brain MRI: a multi-cohort evaluation of 3D architectures for age and sex prediction.Brain informatics · 2026Article
- From Infancy to Aging: Precise Brain Age Estimation via Hybrid CoTResNet3D and CrossViT Models on T1-Weighted Imaging.Bioengineering (Basel, Switzerland) · 2026Article
- Enhancing brain age estimation with structural MRI and synthesized cerebral blood volume maps.Brain communications · 2026Article
- The effect of lesion filling on brain age estimation in multiple sclerosis.BMC medical imaging · 2025Article
- Brain Age Prediction: Deep Models Need a Hand to Generalize.Human brain mapping · 2025Article
- Regional Brain Aging Disparity Index: Region-Specific Brain Aging State Index for Neurodegenerative Diseases and Chronic Disease Specificity.Bioengineering (Basel, Switzerland) · 2025Article
- Do Transformers and CNNs Learn Different Concepts of Brain Age?Human brain mapping · 2025Article
- Network Occlusion Sensitivity Analysis Identifies Regional Contributions to Brain Age Prediction.Human brain mapping · 2025Article
- The utility of explainable AI for MRI analysis: Relating model predictions to neuroimaging features of the aging brain.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- MRI-based whole-brain elastography and volumetric measurements to predict brain age.Biology methods & protocols · 2025Article
- A Survey on Explainable Artificial Intelligence (XAI) Techniques for Visualizing Deep Learning Models in Medical Imaging.Journal of imaging · 2024Article
- 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
- Brain age gap estimation using attention-based ResNet method for Alzheimer's disease detection.Brain informatics · 2024Article
- Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer's disease.Imaging neuroscience (Cambridge, Mass.) · 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
- Article
- MRI-based brain age prediction model for children under 3 years old using deep residual network.Brain structure & function · 2023Article
- Human-to-monkey transfer learning identifies the frontal white matter as a key determinant for predicting monkey brain age.Frontiers in aging neuroscience · 2023Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
Numerous studies have established that estimated brain age constitutes a valuable biomarker that is predictive of cognitive decline and various neurological diseases. In this work, we curate a large-scale brain MRI data set of healthy individuals, on which we train a uniform deep learning model for brain age estimation. We demonstrate an age estimation accuracy on a hold-out test set (mean absolute error = 4.06 years, r = 0.970) and an independent life span evaluation data set (mean absolute error = 4.21 years, r = 0.960). We further demonstrate the utility of the estimated age in a life span aging analysis of cognitive functions. In summary, we achieve age estimation performance comparable to previous studies, but with a more heterogenous data set confirming the efficacy of this deep learning framework. We also evaluated training with varying age distributions. The analysis of regional contributions to our brain age predictions through multiple analyses, and confirmation of the association of divergence between the estimated and chronological brain age with neuropsychological measures, may be useful in the development and evaluation of similar imaging biomarkers.
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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.