AIMC Topic: Brain
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AI-driven fusion of multimodal data for Alzheimer's disease biomarker assessment.
Nature communications
Aug 11, 2025
Alzheimer's disease (AD) diagnosis hinges on detecting amyloid beta (Aβ) plaques and neurofibrillary tau (τ) tangles, typically assessed using PET imaging. While accurate, these modalities are expensive and not widely accessible, limiting their utili...
Improving early detection of Alzheimer's disease through MRI slice selection and deep learning techniques.
Scientific reports
Aug 10, 2025
Alzheimer's disease is a progressive neurodegenerative disorder marked by cognitive decline, memory loss, and behavioral changes. Early diagnosis, particularly identifying Early Mild Cognitive Impairment (EMCI), is vital for managing the disease and ...
Advancements in the investigation of the mechanisms underlying cognitive aging.
Biogerontology
Aug 10, 2025
Cognitive aging, a pivotal domain at the intersection of neuroscience and psychology, exhibits a strong association with neurodegenerative disorders; however, its comprehensive underlying mechanisms remain incompletely elucidated. This review aims to...
Artificial intelligence with feature fusion empowered enhanced brain stroke detection and classification for disabled persons using biomedical images.
Scientific reports
Aug 9, 2025
Brain stroke is an illness which affects almost every age group, particularly people over 65. There are two significant kinds of strokes: ischemic and hemorrhagic strokes. Blockage of brain vessels causes an ischemic stroke, while cracks in blood ves...
Longitudinal structural MRI-based deep learning and radiomics features for predicting Alzheimer's disease progression.
Alzheimer's research & therapy
Aug 7, 2025
BACKGROUND: Alzheimer's disease (AD) is the principal cause of dementia and requires the early diagnosis of people with mild cognitive impairment (MCI) who are at high risk of progressing. Early diagnosis is imperative for optimizing clinical managem...
Circulating epigenetic signatures classifying brain insulin resistance in humans.
Science translational medicine
Aug 6, 2025
Brain insulin action plays an important role in metabolic and cognitive health, but there is no biomarker available to assess brain insulin resistance in humans. Here, we developed a machine learning framework based on blood DNA methylation profiles ...
Dynamic neural network modulation associated with rumination in major depressive disorder: a prospective observational comparative analysis of cognitive behavioral therapy and pharmacotherapy.
Translational psychiatry
Aug 6, 2025
Cognitive behavioral therapy (CBT) and pharmacotherapy are primary treatments for major depressive disorder (MDD). However, their differential effects on the neural networks associated with rumination, or repetitive negative thinking, remain poorly u...
Neural Synchrony and Consumer Behavior: Predicting Friends' Behavior in Real-World Social Networks.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Aug 6, 2025
The endogenous aspect of social influence, reflected in the spontaneous alignment of behaviors within close social relationships, plays a crucial role in understanding human social behavior. In two studies involving 222 human subjects (Study 1: = 17...
PyNoetic: A modular python framework for no-code development of EEG brain-computer interfaces.
PloS one
Aug 6, 2025
Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) have emerged as a transformative technology with applications spanning robotics, virtual reality, medicine, and rehabilitation. However, existing BCI frameworks face several limitati...
Cross-subject EEG signals-based emotion recognition using contrastive learning.
Scientific reports
Aug 3, 2025
Electroencephalography (EEG) signals based emotion brain computer interface (BCI) is a significant field in the domain of affective computing where EEG signals are the cause of reliable and objective applications. Despite these advancements, signific...
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