Neurology

Dementia

Latest AI and machine learning research in dementia for healthcare professionals.

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Speech Acoustic Markers Detect APOE-ε4 Carrier Status in Cognitively Healthy Individuals

APOE-ε4, the strongest genetic risk factor for Alzheimer’s disease (AD), is linked to early motor vu...

Neuro: Machine Learning Optimized to Detect Neurodegenerative Diseases Pilot Study

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder that primarily affects cognitiv...

Predicting future cognitive impairment in preclinical Alzheimer’s disease using multimodal imaging: a multisite machine learning study

Predicting the likelihood of developing Alzheimer’s disease (AD) dementia in at-risk individuals is ...

Alzheimer’s Disease Stage Classification via Multimodal CNN on EEG Spectrograms and Cube-Drawing Images

Clinicians currently lack reliable tools to determine, at the point of mild cognitive impairment (MC...

A new ANMerge-based blood transcriptomic resource to support Alzheimer’s disease research

Alzheimer’s disease (AD) has greater prevalence in women and lacks effective treatments. Integrating...

Quantitative pathology and APOE genotype reveal dementia risk and progression in Lewy body disease

Dementia in Lewy body diseases (LBD) is common and arises through heterogeneous and incompletely und...

Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease Using a Vision Transformer and Hippocampal MRI Slices

Convolutional neural networks (CNNs) have been the standard for computer vision tasks including appl...

Predicting Amyloid Positivity Through Proteomic and Machine Learning Approaches

Alzheimer’s disease is a progressive neurodegenerative disorder where early detection remains diffic...

Regional brain aging patterns reveal disease-specific pathways of neurodegeneration

The heterogeneity of brain aging is a hallmark of neurological and psychiatric disorders, yet machin...

Characterizing Dementia Phenotypes from Unstructured EHR Notes with Generative AI and Interpretable Machine Learning

Dementia encompasses diverse clinical syndromes where diseases of the brain can manifest as impaired...

CSF Proteomics and Machine Learning Reveal Distinct Stages Across the Alzheimer’s Disease Continuum

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by heterogeneous pathophysiol...

Examining public acceptance of AI versus human-centric dementia care across NHS England’s dementia pathway stages

With dementia diagnoses in the UK projected to exceed one million in 2025, there is an urgent need f...

Circulating Metabolites are Linked to Dementia and Brain Imaging Phenotypes, and Mediate Modifiable Risk Pathways

Dementia poses an escalating global health burden, yet its underlying mechanisms remain incompletely...

Sleep Staging Foundation Models Encode Neural Disorder-Related EEG Representations that Generalize to Wakefulness

To leverage sleep foundation models trained on large datasets of polysomnography for neurological di...

A Novel Method to Disentangle Tightly Linked Risk and Resilience Genes for Brain Disorders: Application to Alzheimer’s Disease

Genetic risk factors for neuropsychiatric disorders are well documented. However, some individuals w...

Development of Alzheimer’s Disease Risk Score for Future Primary Care: A White-Box Approach

Interpretable scoring system can contribute to bridge the gap between the timeliness and complexity ...

Machine learning-based prediction of future dementia using routine clinical MRI brain scans and healthcare data

Early identification of dementia risk is essential for preventive care and timely enrolment into dis...

Integrating Infection Burden and Multimodal Biomarkers for Early Detection of Alzheimers Disease: A Sheaf-ML Framework

Alzheimers disease (AD) remains a major global health challenge, with growing evidence linking chron...

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