Machine learning for brain age prediction: Introduction to methods and clinical applications
The rise of machine learning has unlocked new ways of analysing structural neuroimaging
data, including brain age prediction. In this state-of-the-art review, we provide an …
data, including brain age prediction. In this state-of-the-art review, we provide an …
From a deep learning model back to the brain—Identifying regional predictors and their relation to aging
Abstract We present a Deep Learning framework for the prediction of chronological age from
structural magnetic resonance imaging scans. Previous findings associate increased brain …
structural magnetic resonance imaging scans. Previous findings associate increased brain …
Brain age prediction: A comparison between machine learning models using region‐and voxel‐based morphometric data
Brain morphology varies across the ageing trajectory and the prediction of a person's age
using brain features can aid the detection of abnormalities in the ageing process. Existing …
using brain features can aid the detection of abnormalities in the ageing process. Existing …
A deep ensemble hippocampal CNN model for brain age estimation applied to Alzheimer's diagnosis
Age-associated diseases rise as life expectancy increases. The brain presents age-related
structural changes across life, with different extends between subjects and groups. During …
structural changes across life, with different extends between subjects and groups. During …
Age-net: An MRI-based iterative framework for brain biological age estimation
The concept of biological age (BA)-although important in clinical practice-is hard to grasp
mainly due to the lack of a clearly defined reference standard. For specific applications …
mainly due to the lack of a clearly defined reference standard. For specific applications …
Ordinal Classification with Distance Regularization for Robust Brain Age Prediction
Age is one of the major known risk factors for Alzheimer's Disease (AD). Detecting AD early
is crucial for effective treatment and preventing irreversible brain damage. Brain age, a …
is crucial for effective treatment and preventing irreversible brain damage. Brain age, a …
A multitask deep learning model for voxel-level brain age estimation
Global brain age estimation has been used as an effective biomarker to study the correlation
between brain aging and neurological disorders. However, it fails to provide spatial …
between brain aging and neurological disorders. However, it fails to provide spatial …
Predicting brain age using partition modeling strategy and atlas-based attentional enhancement in the Chinese population
Y Wu, Y Chen, Y Yang, C Lin, S Su, J Zhao… - Cerebral …, 2024 - academic.oup.com
As a biomarker of human brain health during development, brain age is estimated based on
subtle differences in brain structure from those under typical developmental. Magnetic …
subtle differences in brain structure from those under typical developmental. Magnetic …
Brain Age Prediction Using a Lightweight Convolutional Neural Network
Background: Much interest has recently been drawn to brain age prediction due to the
significant development in machine learning and image processing techniques. Studies …
significant development in machine learning and image processing techniques. Studies …
Organ-based chronological age estimation based on 3D MRI scans
Individuals age differently depending on a multitude of different factors such as lifestyle,
medical history and genetics. Often, the global chronological age is not indicative of the true …
medical history and genetics. Often, the global chronological age is not indicative of the true …