IEEE journal of biomedical and health informatics
Jan 7, 2025
Predicting the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is critical for early intervention. Towards this end, various deep learning models have been applied in this domain, typically relying on structural magnetic ...
IEEE journal of biomedical and health informatics
Jan 7, 2025
Emerging researchindicates that the degenerative biomarkers associated with Alzheimer's disease (AD) exhibit a non-random distribution within the cerebral cortex, instead following the structural brain network. The alterations in brain networks occur...
Alzheimer's disease (AD), a progressive neurodegenerative condition, notably impacts cognitive functions and daily activity. One method of detecting dementia involves a task where participants describe a given picture, and extensive research has been...
Alzheimer's disease (AD) is a prototypical neurodegenerative disorder, predominantly affecting individuals in the presenile and elderly populations, with an etiology that remains elusive. This investigation aimed to elucidate the alterations in anoik...
The rising incidence of Alzheimer's disease (AD) poses significant challenges to traditional diagnostic methods, which primarily rely on neuropsychological assessments and brain MRIs. The advent of deep learning in medical diagnosis opens new possibi...
The diagnosis of neurological diseases can be expensive, invasive, and inaccurate, as it is often difficult to distinguish between different types of diseases with similar motor symptoms. However, the dysregulation of miRNAs can be used to create a r...
The linear mixed-effects model is commonly utilized to interpret longitudinal data, characterizing both the global longitudinal trajectory across all observations and longitudinal trajectories within individuals. However, characterizing these traject...
The interconnection between brain regions in neurological disease encodes vital information for the advancement of biomarkers and diagnostics. Although graph convolutional networks are widely applied for discovering brain connection patterns that poi...
The journal of prevention of Alzheimer's disease
Jan 1, 2025
BACKGROUND: Protein abundance levels, sensitive to both physiological changes and external interventions, are useful for assessing the Alzheimer's disease (AD) risk and treatment efficacy. However, identifying proteomic prognostic markers for AD is c...
DNA methylation (DNAm) is essential for brain development and function and potentially mediates the effects of genetic risk variants underlying brain disorders. We present INTERACT, a transformer-based deep learning model to predict regulatory varian...