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classification
842 studies tagged classification, dated 1983-08-01 to 2026-09-25. Bibliography: BibTeX (.bib) · RIS (.ris)
Newest in this topic
- Diagnostic accuracy of remote self-administered digital cognitive assessment by clinical diagnosis and Alzheimer's disease PET imaging biomarkers 2026-09-25
- Multi-scale 3D CNN with imbalance-aware training for structural MRI-based six-class Alzheimer disease staging 2026-09-22
- T1 mapping in Alzheimer’s disease: a quantitative MRI study with amyloid-PET correlation 2026-09-21
Studies
842 studies carry this tag.
Date range
1983 to 2026
Top journals
- Neurology 83
- Journal of nuclear medicine : official publication, Society of Nuclear Medicine 42
- Brain : a journal of neurology 34
- NeuroImage 31
- Alzheimer s & Dementia 30
283 journals in all.
Newest first, then by address. Each study has a usefulness score out of 100 (rubric version 4.0); tap a score to see what makes it up. Tags were assigned automatically from each study's title and summary. The same studies as a filter in the library.
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Alzheimer’s disease (AD) is a neurodegenerative disorder that affects millions of people worldwide.
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Alzheimer’s disease (AD) is the most common cause of dementia, emphasizing the critical need for the development of biomarkers that facilitate accurate and objective assessment of disease progression for early detection and intervention to delay its onset.
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This study classified preclinical Alzheimer's disease (AD) using cognitive screening, neighborhood deprivation via the area deprivation index (ADI), and sociodemographic and genetic risk factors.
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41/100
IRMA can be used to learn and disregard center-specific information in features extracted from brain $$^{18}$$ 18 F-FDG PET scans, while retaining disease-specific information.
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Alzheimer's Disease (AD) is a progressive condition of a neurological brain disorder recognized by symptoms such as dementia, memory loss, alterations in behaviour, and impaired reasoning abilities.
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BackgroundA novel neuroimaging signature of regional cortical thickness on brain MRI recently showed high potential for Alzheimer's disease and related dementias (ADRD) risk stratification in the community.
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Alzheimer's Disease (AD) is a particular form of dementiacharacterized by a steady decline in brain function and cognitive abilities, leading to memory loss, disorientation, and trouble doing daily tasks.
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After controlling for the level of cognitive impairment, we found a double dissociation between AD clinical phenotype and localization/magnitude of atrophy, characterized by predominant neocortical involvement in EOAD and more focal anterior medial temporal involvement in LOAD.
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AD patients exhibited a significant reduction in the water exchange rates across the BBB, whereas DLB patients showed a significant increase in BBB permeability to contrast agent.
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In this study, we present a comprehensive pipeline to train and compare a broad spectrum of machine learning and deep learning brain clocks, integrating diverse preprocessing strategies and correction terms.
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The left inferior parietal lobule (IPL)_6_5 (rostroventral area 39) showed the best ability to discriminate between patients with AD and those with CN (AUC = 0.688).
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Data from 262 records (260 unique participants) were analyzed.
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As the leading cause of dementia worldwide, Alzheimer’s Disease (AD) has prompted significant interest in developing Deep Learning (DL) approaches for its classification.
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Utilizing clinical data, the highest ROC AUC scores attained were 0.989, 0.927, and 0.907 for the identification of the CN, MCI, and dementia stages, respectively.
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Model scores two standard deviations below the mean had 4 months increased survival (two standard deviations below had 3 months decreased survival).
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Significant amygdala atrophy was observed in multiple amygdala nuclei across cognitive performance groups, with more pronounced changes in the low-performance group.
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A total of 13,659 articles were obtained in this study.
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Amyloid-targeting therapy has recently become widely available in the United States for the treatment of patients with symptomatic mild Alzheimer disease (AD).
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64/100
Our findings revealed distinct patterns of connectivity linked to normal ageing or Alzheimer's disease.
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IntroductionThe prevalence of neurodegenerative diseases has significantly increased, necessitating a deeper understanding of their symptoms, diagnostic processes, and prevention strategies.
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Florbetaben (FBB) is a radiopharmaceutical approved by the FDA and EMA in 2014 for the positron emission tomography (PET) imaging of brain amyloid deposition in patients with cognitive impairment who are being evaluated for Alzheimer's disease (AD) or other causes of cognitive decline.
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The rising incidence of Alzheimer's disease (AD) poses significant challenges to traditional diagnostic methods, which primarily rely on neuropsychological assessments and brain MRIs.
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39/100
[18F]GTP1 exhibited retention patterns that correlated with [18F]PI-2620 and [18F]MK-6240 for all Braak regions (except Braak II).
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Alzheimer’s disease (AD) presents a significant global health challenge, necessitating accurate and early prediction methods for effective intervention and treatment planning.
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25/100
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25/100
This survey presents 50 research papers focussed on various techniques in Alzheimer classification techniques using 3D MRI images, and the categorisation of the techniques is made based on the fusion-based, convolutional neural network (CNN)-based, random forest (RF)-based and support vector machine (SVM)-based approaches.
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33/100
Conventional dementia screening tools, whether paper tests or static artificial intelligence (AI) models, capture only a snapshot of cognition and need to be adminstered periodically.
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This special issue of Alzheimer's & Dementia celebrates the accomplishments of the Alzheimer's Disease Neuroimaging Initiative (ADNI) project as it approaches its 20th anniversary in 2024, supported by funding from the National Institute on Aging.
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Alzheimer’s disease (AD), a leading neurodegenerative disorder, progresses from an intermediary stage known as Mild Cognitive Impairment (MCI), characterized by measurable cognitive decline with retained functional independence.
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40/100
Alzheimer's disease (AD) and frontotemporal dementia (FTD) are the most burdensome neurodegenerative disorders in older populations as they pose significant challenges because of subtle cognitive decline in the initial stages.
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Neurological disorders are among the leading causes of both physical and cognitive disabilities worldwide, affecting approximately 15% of the global population.
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Finally, we showed that the MD-MRI-derived astrogliosis biomarker is the only MRI measure capable of predicting cognitive state.
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Alzheimer’s disease (AD) is a progressive neurological condition that leads to dementia.
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Researchers tested whether a tablet-based cognitive test (TabCAT) could substitute for traditional paper-and-pencil memory tests in people with early-onset Alzheimer's. Scores on the tablet's attention/executive tasks correlated strongly (above 0.7) with standard tests like the MMSE and MoCA, and one subtest could distinguish people with amyloid plaques from those without with good accuracy (AUC 0.82).
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Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care assessment of patients with Alzheimer's disease (AD) in settings where conventional MRI cannot.
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The Alzheimer's Disease Neuroimaging Initiative (ADNI) has fostered collaboration among researchers around the world, catalyzing innovation and accelerating progress in the field.
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The patient was participating in an extended open-label trial of aducanumab when she was admitted to hospital for focal seizures and ARIA in 2 noncontiguous regions of the left frontal and occipital lobes.
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These findings indicate EXT may be more sensitive to Aβ's role in preclinical AD than level and improve targeting of individuals for AD prevention trials.
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Our results demonstrate that unsupervised digital memory assessments might be used for diagnosis and prognosis in Alzheimer's disease, potentially in combination with plasma biomarkers.
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53/100
Alzheimer's disease (AD) accounts for 60-70% of the population with dementia.
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This study summarizes the existing literature on TSPO expression in specific regions of the brain in patients with dementia, and also provides some preliminary evidence on the possible association between neuroinflammation and dementia.
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Since the development of amyloid tracers for PET imaging, there has been interest in quantifying amyloid burden in the brains of patients with Alzheimer disease.
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ARIA monitoring is important to inform treatment dosing decisions and might be improved through assistive software.
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Alzheimer disease (AD) is primarily associated with accumulations of amyloid plaques and tau tangles in gray matter, however, it is now acknowledged that neuroinflammation, particularly in white matter (WM), significantly contributes to the development and progression of AD.
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We found that ML-PRS approaches improved upon standard PRS for prediction of AD endophenotypes, partly related to improved accounting for nonlinear effects of genetic susceptibility alleles.
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To ensure diversity, we developed a comprehensive recruitment strategy using a diverse, culturally‐trained staff that includes : • Identifying Dementia Specialists experienced recruiting minorities • Embedding high‐impact community engagement in select regions • Increasing capacity of specialists and PET facilities to engage minorities • Increasing pipeline of referrals to Dementia Specialists • Creating a culturally‐informed awareness campaign Result New IDEAS has enrolled 4,524 participants including 954 (21.1%) Black/African American, and 842 (18.6%) Hispanic/Latinx.
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It is imperative to recognize and mitigate persistent disparities in the COVID‐19 pandemic, particularly pertaining to participation in long‐COVID research.
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47/100
Alzheimer disease (AD) is the most common form of dementia worldwide.
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Alzheimer's disease (AD) is the most common cause of dementia worldwide, but the molecular and cellular mechanisms underlying cognitive impairment remain poorly understood.
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71/100
The literature has several methodological limitations including lack of sufficient algorithm development descriptions and standard definitions.
From across this tag
8 of the 838 studies in this tag, 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 8. The same 8 appear here every time.
- Quantitative assessment of synaptic density in the outer molecular layer of the hippocampal dentate gyrus in Alzheimer's disease
- Predicting Prodromal Alzheimer's Disease in Subjects with Mild Cognitive Impairment Using Machine Learning Classification of Multimodal Multicenter Diffusion-Tensor and Magnetic Resonance Imaging Data
- Neuroinflammation and Functional Connectivity in Alzheimer's Disease: Interactive Influences on Cognitive Performance
- Incidence of Amyloid-Related Imaging Abnormalities in Patients With Alzheimer Disease Treated With Anti-β-Amyloid Immunotherapy: A Meta-analysis
- Clinical and pathologic correlations of machine learning quantification of Aβ deposits across 3 brain regions of decedents with Alzheimer disease
- Identification of famous faces and famous names in early Alzheimer's disease. Relationship to anterograde episodic and general semantic memory
- An MRI measure of degenerative and cerebrovascular pathology in Alzheimer disease
- Choroid Plexus Volume and Permeability at Brain MRI within the Alzheimer Disease Clinical Spectrum