Alzheimer's Disease

Electroencephalogram features support the retrogenesis hypothesis of Alzheimer's disease: Exploratory comparison of brain changes in aging and childhood.

BackgroundThe retrogenesis hypothesis (RH) suggests that the functional and cognitive decline observed in Alzheimer's disease dementia mirrors in reverse order the brain development during childhood and adolescence.ObjectiveEquivalent electroencephalogram (EEG) patterns between older adults across different cognitive decline stages and children across different brain maturation stages were directl...

Cognition-Eye-Brain Connection in Alzheimer's Disease Spectrum Revealed by Multimodal Imaging.

BACKGROUND: The connection between cognition, eye, and brain remains inconclusive in Alzheimer's disease (AD) spectrum disorders.

An FDG-PET-Based Machine Learning Framework to Support Neurologic Decision-Making in Alzheimer Disease and Related Disorders.

BACKGROUND AND OBJECTIVES: Distinguishing neurodegenerative diseases is a challenging task requiring neurologic expertise. Clinical decision support s...

Utility of machine learning algorithms in classification of progressive cognitive impairment in Alzheimer's disease: A retrospective cohort based on China.

BackgroundDistinct risk factors influence Alzheimer's disease (AD) stage stratification, yet effective tools for early diagnosis and prognosis remain ...

Difference between eyes-open and eyes-closed resting state quantitative electroencephalography (qEEG) for predicting cognitive impairment using deep learning.

OBJECTIVE: Electroencephalography (EEG) is a method that offers detailed observations of electrical activities occurring in the brain's cerebral corte...

Deep Learning-Based Prediction of PET Amyloid Status Using MRI.

BACKGROUND AND PURPOSE: Identifying amyloid-beta (Aβ)-positive patients is essential for Alzheimer's disease (AD) clinical trials and disease-modifyin...

Plasma lipidomic fingerprinting enables high-accuracy biomarker discovery for Alzheimer's disease: a targeted LC-MRM/MS approach.

Dysregulation of lipid metabolism is increasingly recognized as a key factor in the pathogenesis of Alzheimer's disease (AD). Unfortunately, an accura...

γ neuromodulations: unraveling biomarkers for neurological and psychiatric disorders.

γ neuromodulation has emerged as a promising strategy for addressing neurological and psychiatric disorders, particularly in regulating executive and ...

Development and validation of a combined clinical and MRI-based biomarker model to differentiate mild cognitive impairment from mild Alzheimer's disease.

BACKGROUND: Two of the most common complaints seen in neurology clinics are Alzheimer's disease (AD) and mild cognitive impairment (MCI), characterize...

Development of an anomaly detection system for Gibbs artifact identification in amyloid PET imaging.

The PET Imaging Site Qualification Program for amyloid positron emission tomography (PET) in Japan includes visual evaluation of the cylinder phantom....

Association of peripheral immune markers with brain age and dementia risk estimated using deep learning methods.

BACKGROUND: The peripheral immune system is essential for maintaining central nervous system homeostasis. This study investigates the effects of perip...

Novel insights from comprehensive analysis: The role of cuproptosis and peripheral immune infiltration in Alzheimer's disease.

BACKGROUND: Cuproptosis is increasingly recognized as an essential factor in the pathological process of Alzheimer's disease (AD). However, the specif...

Temporal Dynamics of APOE and TREM2 Expression in Microglial Activation of NMOSD Mouse Models.

Neuromyelitis optica spectrum disorder (NMOSD) is a severe autoimmune demyelinating disease characterized by recurrent neuroinflammation and disabilit...

Exploring Factors Related to Social Isolation Among Older Adults in the Predementia Stage Using Ecological Momentary Assessments and Actigraphy: Machine Learning Approach.

BACKGROUND: As the global population ages, the economic burden of dementia continues to rise. Social isolation-which includes limited social interacti...

Machine learning-based prediction of amyloid positivity using early-phase F-18 flutemetamol PET.

BackgroundPrevious studies have suggested that early-phase imaging of amyloid positron emission tomography (PET) may offer information for predicting ...

Uncovering injury-specific proteomic signatures and neurodegenerative risks in single and repetitive traumatic brain injury.

Traumatic brain injury (TBI) is a major public health concern associated with an increased risk of neurodegenerative diseases including Alzheimer's di...

Graph_RG: Dominating CASP16's Small Molecule Affinity Prediction Subcategory-A Pose-Free Framework for Billion-Scale Virtual Screening.

Protein-ligand interaction prediction is pivotal in early-stage drug development, enabling large-scale virtual screening, drug optimization, and rever...

A New Insight in Cellular and Molecular Signaling Regulation for Neural Differentiation Program.

Numerous neurological conditions impact the brain, spinal cord, and nerves, including neurodegenerative diseases such as Alzheimer's and Parkinson's d...

The Rapid Online Cognitive Assessment for the Detection of Neurocognitive Disorder: Open-Label Study.

BACKGROUND: The rising prevalence of dementia necessitates a scalable solution to cognitive screening. Paper-based cognitive screening examinations ar...

Explainable AI predicting Alzheimer's disease with latent multimodal deep neural networks.

PURPOSE: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline. We proposed a novel latent multimoda...