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 …
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 …
MM Rahman, F Islam, S Afsana Mim… - Journal of …, 2022 - Wiley Online Library
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 …
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 …
Background: Neuroimage analysis has made it possible to perform various anatomical analyses of the brain regions and helps detect different brain conditions/disorders. Recently …
Neuroimaging-driven brain age estimation has introduced a robust (reliable and heritable) biomarker for detecting and monitoring neurodegenerative diseases. Here, we computed …
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 …
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 …
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 …