Deep learning for brain age estimation: A systematic review
Abstract Over the years, Machine Learning models have been successfully employed on
neuroimaging data for accurately predicting brain age. Deviations from the healthy brain …
neuroimaging data for accurately predicting brain age. Deviations from the healthy brain …
The use of neuroimaging techniques in the early and differential diagnosis of dementia
L Chouliaras, JT O'Brien - Molecular Psychiatry, 2023 - nature.com
Dementia is a leading cause of disability and death worldwide. At present there is no
disease modifying treatment for any of the most common types of dementia such as …
disease modifying treatment for any of the most common types of dementia such as …
Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations
Brain clocks, which quantify discrepancies between brain age and chronological age, hold
promise for understanding brain health and disease. However, the impact of diversity …
promise for understanding brain health and disease. However, the impact of diversity …
Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment
The gap between chronological age (CA) and biological brain age, as estimated from
magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging …
magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging …
Deep learning-based diagnosis of Alzheimer's disease
Alzheimer's disease (AD), the most familiar type of dementia, is a severe concern in modern
healthcare. Around 5.5 million people aged 65 and above have AD, and it is the sixth …
healthcare. Around 5.5 million people aged 65 and above have AD, and it is the sixth …
Brain aerobic glycolysis and resilience in Alzheimer disease
The distribution of brain aerobic glycolysis (AG) in normal young adults correlates spatially
with amyloid-beta (Aβ) deposition in individuals with symptomatic and preclinical Alzheimer …
with amyloid-beta (Aβ) deposition in individuals with symptomatic and preclinical Alzheimer …
Association of white matter volume with brain age classification using deep learning network and region wise analysis
Structural magnetic resonance imaging (sMRI) has been used to examine age-related
neuroanatomical changes in the human brain. In the present work, a pre-trained deep …
neuroanatomical changes in the human brain. In the present work, a pre-trained deep …
A perspective on brain-age estimation and its clinical promise
Brain-age estimation has gained increased attention in the neuroscientific community owing
to its potential use as a biomarker of brain health. The difference between estimated and …
to its potential use as a biomarker of brain health. The difference between estimated and …
Prediction of mechanistic subtypes of Parkinson's using patient-derived stem cell models
K D'Sa, JR Evans, GS Virdi, G Vecchi, A Adam… - Nature Machine …, 2023 - nature.com
Parkinson's disease is a common, incurable neurodegenerative disorder that is clinically
heterogeneous: it is likely that different cellular mechanisms drive the pathology in different …
heterogeneous: it is likely that different cellular mechanisms drive the pathology in different …
Histopathologic brain age estimation via multiple instance learning
GA Marx, J Kauffman, AT McKenzie… - Acta …, 2023 - Springer
Understanding age acceleration, the discordance between biological and chronological
age, in the brain can reveal mechanistic insights into normal physiology as well as elucidate …
age, in the brain can reveal mechanistic insights into normal physiology as well as elucidate …