Each study has a usefulness score out of 100 (rubric version 4.0). Tap a score to see what makes it up.
Highest usefulness score first. Studies without a score come last.
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Apathy and depression are among the most common neuropsychiatric symptoms in dementia.
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Multimodal integration of cognitive, neuroimaging, and polygenic data in the MHS-RWD tool yields strong discrimination for both early diagnosis of dementia and AD differential diagnosis.
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In dialect-dominant, educationally diverse elderly, Mini-cog provides superior diagnostic accuracy for MCI versus HKBC and MoCA, and comparable accuracy for dementia.
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Sleeping more than one’s usual average the night before testing was associated with better delayed memory ( β = 0.03, p = 0.02), while no between-person sleep effects emerged.
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The present work builds upon progress in foundation artificial intelligence (AI) models for thepurpose of supporting the Alzheimer’s Disease Neuroimaging Initiative (ADNI).
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16/100
In a contemporary, diverse cohort, most established dementia risk algorithms had limited power in discriminating amyloid positivity, pTau-217 positivity, and current cognitive status despite acceptable calibration.
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Artificial intelligence (AI) is now a credible translational research platform across the Alzheimer’s disease (AD) pathway, but its clinical value is often difficult to judge from performance metrics alone.
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Irrespective of ERG modality, ADRD was consistently associated with retinal dysfunction marked by impaired synaptic transmission and delayed neural processing across retinal circuits.
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Population ageing is accelerating globally, with a rising burden of neurocognitive disorders such as dementia and Alzheimer’s disease, particularly in low- and middle-income countries.
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Specific disease clusters involving diabetes, oral disease, sensory impairment, and osteoporosis were associated with suspected dementia and neuropsychiatric heterogeneity, supporting integrated multimorbidity-oriented screening and care.
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AD prevention must transcend the "geriatric disease" mindset.
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Traumatic brain injury (TBI) is the main cause of death and disability in the United States in people younger than 35 years old and is a common cause of wartime injuries.
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Detection and characterisation of dementia and Mild Cognitive Impairment (MCI) is essential for diagnosis and to support recruitment of patients into trials of disease-targeted therapies.
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Recent advances in blood-based biomarkers have transformed the early diagnosis of Alzheimer’s disease (AD), enabling the identification of biological risk at preclinical and presymptomatic stages in a noninvasive and accessible manner.
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Early, scalable detection of Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains a global health priority, but non-invasive biomarkers that capture network-level dysfunction during standardized cognitive challenge remain limited.
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When stable individual differences are accounted for, depressive symptoms emerge as a stronger within-person temporal predictor of cognitive decline than physical activity.
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Cognitive impairment is a prevalent symptom extending from physiological ageing to disease.
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We recommend using a broad (ADRD) algorithm without CMS or medication data, particularly for epidemiological studies or a strict AD algorithm including CMS and medication cases for genetic discovery of late-onset AD associations in VA EMR, and a strict AD algorithm without CMS data for applications focused solely on AD and sensitive to misspecification.
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Structured Abstract Background Alzheimer’s disease (AD) neuropathology emerges decades before symptoms, requiring sensitive, non-invasive markers for early diagnosis.
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Engaging 55 research staff across 25 sites and 3 physician-reviewers, this study is the first to demonstrate feasibility of a VANE as an efficient neurological examination model enabled by commonly used devices.
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Agitation days showed higher median sample entropy (1.23 vs 1.06; p<0.001) and approximate entropy (1.24 vs 1.08; p<5 × 10−19).
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Multidomain interventions have small but consistent beneficial effects on cognitive measures, suggesting the potential to reduce cognitive impairment and dementia risk.
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Default thresholds yielded 20–23% precision with 94– 100% recall—unacceptable for caregiver-facing alerts.
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Recent research has revealed that linguistic features are effective digital markers for the early detection of Alzheimer’s disease (AD).
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16/100
Diffusion MRI (dMRI) enables assessment of white matter microstructural abnormalities in Alzheimer's disease (AD), and multisite datasets enable more robust modeling of non-biological variation that can confound analyses.
From across this topic
10 of the 1,533 studies in this topic, picked by a fixed rule (a hash of each study's address), not by score or date; each page of this list shows a different 10. The same 10 appear here every time.
- Disruption of large-scale brain systems in advanced aging
- Central autonomic network dysfunction and plasma Alzheimer's disease biomarkers in older adults
- Pattern of cerebral hypoperfusion in Alzheimer disease and mild cognitive impairment measured with arterial spin-labeling MR imaging: initial experience
- Intrinsic connectivity networks in posterior cortical atrophy: A role for the pulvinar?
- BEaST: brain extraction based on nonlocal segmentation technique
- Connected Speech in Neurodegenerative Language Disorders: A Review
- Visual impairment and cognitive dysfunction in Alzheimer's disease
- Frequency-Dependent Altered Functional Connections of Default Mode Network in Alzheimer's Disease
- Effective differentiation of mild cognitive impairment by functional brain graph analysis and computerized testing
- Associations between sleep duration and cognitive impairment in mild cognitive impairment