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 …
Factors associated with brain ageing-a systematic review
Background Brain age is a biomarker that predicts chronological age using neuroimaging
features. Deviations of this predicted age from chronological age is considered a sign of age …
features. Deviations of this predicted age from chronological age is considered a sign of age …
Predicting brain age using machine learning algorithms: A comprehensive evaluation
Machine learning (ML) algorithms play a vital role in the brain age estimation frameworks.
The impact of regression algorithms on prediction accuracy in the brain age estimation …
The impact of regression algorithms on prediction accuracy in the brain age estimation …
[Retracted] Multifunctional Therapeutic Approach of Nanomedicines against Inflammation in Cancer and Aging
Cancer is a fatal disorder that affects people across the globe, yet existing therapeutics are
ineffective. The development of submicrometer transport for optimizing the biodistribution of …
ineffective. The development of submicrometer transport for optimizing the biodistribution of …
Cardiometabolic risk factors associated with brain age and accelerated brain ageing
The structure and integrity of the ageing brain is interchangeably linked to physical health,
and cardiometabolic risk factors (CMRs) are associated with dementia and other brain …
and cardiometabolic risk factors (CMRs) are associated with dementia and other brain …
A review of neuroimaging-driven brain age estimation for identification of brain disorders and health conditions
Background: Neuroimage analysis has made it possible to perform various anatomical
analyses of the brain regions and helps detect different brain conditions/disorders. Recently …
analyses of the brain regions and helps detect different brain conditions/disorders. Recently …
[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 …
Deep learning of brain magnetic resonance images: A brief review
Magnetic resonance imaging (MRI) is one of the most popular techniques in brain science
and is important for understanding brain function and neuropsychiatric disorders. However …
and is important for understanding brain function and neuropsychiatric disorders. However …
Clinical application of machine learning models for brain imaging in epilepsy: a review
D Sone, I Beheshti - Frontiers in Neuroscience, 2021 - frontiersin.org
Epilepsy is a common neurological disorder characterized by recurrent and disabling
seizures. An increasing number of clinical and experimental applications of machine …
seizures. An increasing number of clinical and experimental applications of machine …
Total sleep deprivation increases brain age prediction reversibly in multisite samples of young healthy adults
C Chu, SC Holst, EM Elmenhorst… - Journal of …, 2023 - Soc Neuroscience
Sleep loss pervasively affects the human brain at multiple levels. Age-related changes in
several sleep characteristics indicate that reduced sleep quality is a frequent characteristic …
several sleep characteristics indicate that reduced sleep quality is a frequent characteristic …