This is the first demonstration that MRI-informed brain age models exhibit feature-specific patterns. The greater GMV-based brain age observed in MCI converters may provide new evidence for identifying the individuals at the early stage of neurodegeneration. Our findings added value to existing quantitative imaging markers and might help to improve disease monitoring and accelerate personalized treatments in clinical practice.
Keyphrases
- mild cognitive impairment
- machine learning
- early stage
- resting state
- white matter
- cognitive decline
- clinical practice
- magnetic resonance imaging
- high resolution
- contrast enhanced
- functional connectivity
- cerebral ischemia
- deep learning
- computed tomography
- artificial intelligence
- brain injury
- subarachnoid hemorrhage
- neural network