Dementia

Multi-Orientation Hippocampus-Centered 3D CNN with Attention Mechanism for Alzheimer’s Disease Classification from MRI Scans

Alzheimer’s disease detection faces challenges in capturing hippocampal atrophy across multiple anatomical orientations. This study presents a multi-orientation hippocampus-centered 3D CNN with attention mechanism for automated classification. The architecture processes three parallel 40×128×128×1 volumes from sagittal, axial, and coronal orientations. Each branch employs Conv3D layers with dilate...

Cascaded Multimodal Deep Learning in the Differential Diagnosis, Progression Prediction, and Staging of Alzheimer’s and Frontotemporal Dementia

Dementia is a complex condition whose multifaceted nature poses significant challenges in the diagnosis, prognosis, and treatment of patients. Despite the availability of large open-source data fueling a wealth of promising research, effective translation of preclinical findings to clinical practice remains difficult. This barrier is largely due to the complexity of unstructured and disparate prec...

CharMark: A Markov Approach to Linguistic Biomarkers in Dementia

Dementia, one of the most prevalent neurodegenerative diseases, affects millions worldwide. Understanding linguistic markers of dementia is crucial fo...

A 60-Second Interpretable Voice Model for Early Dementia Screening

Early detection of cognitive impairment in assisted living is hindered by time-intensive tools like MMSE and MoCA. We present a 60-second voice-based ...

Multimodal Integration of Alzheimer’s Plasma Biomarkers, MRI, and Genetic Risk for Individual Prediction of Cerebral Amyloid Burden

Alzheimer’s disease (AD), the most prevalent neurodegenerative disorder, is marked by the accumulation of amyloid-β (Aβ) plaques. Although cerebral Aβ...

Multivariate whole brain neurodegenerative-cognitive-clinical severity mapping in the Alzheimer’s disease continuum using explainable AI

Neurodegeneration and cognitive impairment are commonly reported in Alzheimer’s disease (AD); however, their multivariate links are not well understoo...

Improving Responsiveness in Game-based Cognitive Assessment for Mild Cognitive Impairment

Mild Cognitive Impairment (MCI) affects up to 20% of older adults and often progresses to dementia. While brief cognitive screening tools like the Mon...

Large-scale plasma proteomics uncovers preclinical molecular signatures of Parkinson’s disease and overlap with other neurodegenerative disorders

Parkinson’s disease (PD) remains incurable, with a long preclinical phase currently undetectable by existing methods. In the largest proteomic study i...

Automatic screening and characterization of patients with acquired neurological conditions from language

Individuals with left-hemisphere damage (LHD), right-hemisphere damage (RHD), dementia, mild cognitive impairment (MCI), traumatic brain injury (TBI),...

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic ph...

Postmortem Validation of Quantitative MRI for White Matter Hyperintensities in Alzheimer’s Disease

White matter hyperintensities (WMH) are frequently observed on MRI in aging and Alzheimer’s disease (AD), yet their microstructural pathology remains ...

BrainSignsNET: Deep Learning-Based 3D Anatomical Landmark Detection in Human Brain Imaging

Accurate detection of anatomical landmarks in brain Magnetic Resonance Imaging (MRI) scans is essential for reliable spatial normalization, image alig...

Artificial intelligence applications for dementia: A systematic review for clinical research

Artificial intelligence and emerging technologies are driving a transformative shift in society, particularly in the healthcare sector, where they enh...

Identifying Sex-Specific Sub-phenotypes of Alzheimer’s Disease Progression Using Longitudinal Electronic Health Records

Alzheimer’s Disease (AD) is a complex neurodegenerative disorder strongly influenced by sex differences, with women comprising nearly two-thirds of ca...

Integrating Machine Learning Pipelines for Multimodal Biomarker Prediction in Alzheimer’s and Parkinson’s Disease: A Component of the Neurodiagnoses Framework

Alzheimer’s and Parkinson’s diseases are age-related neurodegenerative diseases that often require invasive procedures for diagnosis. Traditional diag...

Spatial Distribution and Associated Factors Influencing 2024 Measles-Rubella Vaccination Campaign Coverage among Children Aged 9–59 Months in Mainland Tanzania

Globally, measles remains a major cause of child mortality, and rubella is the leading cause of birth defects among all infectious diseases. In Mainla...

Accelerometer-measured weekend catch-up sleep and incident dementia: a prospective cohort study

To investigate whether accelerometer-measured weekend catch-up sleep, defined as extending sleep on weekends to compensate for weekday sleep inadequac...

A deep learning algorithm based on fundus photographs to measure retinal vascular parameters and their additional value beyond the CAIDE risk score for predicting 14-year dementia risk

Retinal photography is a valuable non-invasive tool for assessing the nature of vessel changes. It is of interest whether retinal vascular parameters ...

Multi-organ AI Endophenotypes Chart the Heterogeneity of Pan-disease in the Brain, Eye, and Heart

Disease heterogeneity and commonality pose significant challenges to precision medicine, as traditional approaches frequently focus on single disease ...

Evaluating the Generalizability of EEG-Based AI Models in Alzheimer’s and Dementia Diagnosis

We thoroughly investigated the generalizability of deep learning models trained on electroencephalography (EEG) data to detect Alzheimer’s disease and...