Brain age vector: A measure of brain aging with enhanced neurodegenerative disorder specificity
Neuroimaging‐driven brain age estimation has become popular in measuring brain aging
and identifying neurodegenerations. However, the single estimated brain age (gap) …
and identifying neurodegenerations. However, the single estimated brain age (gap) …
Predicting brain-age from multimodal imaging data captures cognitive impairment
The disparity between the chronological age of an individual and their brain-age measured
based on biological information has the potential to offer clinically relevant biomarkers of …
based on biological information has the potential to offer clinically relevant biomarkers of …
Mind the gap: Performance metric evaluation in brain‐age prediction
Estimating age based on neuroimaging‐derived data has become a popular approach to
developing markers for brain integrity and health. While a variety of machine‐learning …
developing markers for brain integrity and health. While a variety of machine‐learning …
[HTML][HTML] T1-weighted MRI-driven brain age estimation in Alzheimer's disease and Parkinson's disease
Neuroimaging-driven brain age estimation has introduced a robust (reliable and heritable)
biomarker for detecting and monitoring neurodegenerative diseases. Here, we computed …
biomarker for detecting and monitoring neurodegenerative diseases. Here, we computed …
Investigating the temporal pattern of neuroimaging-based brain age estimation as a biomarker for Alzheimer's Disease related neurodegeneration
Neuroimaging-based brain-age estimation via machine learning has emerged as an
important new approach for studying brain aging. The difference between one's estimated …
important new approach for studying brain aging. The difference between one's estimated …
The Choice of Machine Learning Algorithms Impacts the Association between Brain-Predicted Age Difference and Cognitive Function
WH Lee - Mathematics, 2023 - mdpi.com
Machine learning has been increasingly applied to neuroimaging data to compute
personalized estimates of the biological age of an individual's brain (brain age). The …
personalized estimates of the biological age of an individual's brain (brain age). The …
Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer's Disease and …
I Cumplido-Mayoral, M García-Prat, G Operto, C Falcon… - Elife, 2023 - elifesciences.org
Brain-age can be inferred from structural neuroimaging and compared to chronological age
(brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in …
(brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in …
Benchmarking the generalizability of brain age models: Challenges posed by scanner variance and prediction bias
Abstract Machine learning has been increasingly applied to neuroimaging data to predict
age, deriving a personalized biomarker with potential clinical applications. The scientific and …
age, deriving a personalized biomarker with potential clinical applications. The scientific and …
Brain structure ages—A new biomarker for multi‐disease classification
Age is an important variable to describe the expected brain's anatomy status across the
normal aging trajectory. The deviation from that normative aging trajectory may provide …
normal aging trajectory. The deviation from that normative aging trajectory may provide …
Improved prediction of brain age using multimodal neuroimaging data
Brain age prediction based on imaging data and machine learning (ML) methods has great
potential to provide insights into the development of cognition and mental disorders. Though …
potential to provide insights into the development of cognition and mental disorders. Though …