AIMC Topic: Alzheimer Disease

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Predicting and preventing Alzheimer's disease.

Science (New York, N.Y.)
With all the advances in both the science of aging and artificial intelligence (AI), we are in a propitious position to accurately and precisely determine who is at high risk of developing Alzheimer's disease years before signs of even mild cognitive...

Deep learning-based CAD system for Alzheimer's diagnosis using deep downsized KPLS.

Scientific reports
Alzheimer's disease (AD) is the most prevalent type of dementia. It is linked with a gradual decline in various brain functions, such as memory. Many research efforts are now directed toward non-invasive procedures for early diagnosis because early d...

Diagnostic performance of actigraphy in Alzheimer's disease using a machine learning classifier - a cross-sectional memory clinic study.

Alzheimer's research & therapy
BACKGROUND: Movement patterns, activity levels and circadian rhythm are altered in Alzheimer's disease (AD) and can be assessed by actigraphy using wearable sensors. We aimed to determine the diagnostic performance of actigraphy in AD in a memory cli...

MRI-based diagnostic model for Alzheimer's disease using 3D-ResNet.

Biomedical physics & engineering express
Alzheimer's disease (AD), a progressive neurodegenerative disorder, is the leading cause of dementia worldwide and remains incurable once it begins. Therefore, early and accurate diagnosis is essential for effective intervention. Leveraging recent ad...

Translational approach for dementia subtype classification using convolutional neural network based on EEG connectome dynamics.

Scientific reports
Dementia spectrum disorders, characterized by progressive cognitive decline, pose a significant global health burden. Early screening and diagnosis are essential for timely and accurate treatment, improving patient outcomes and quality of life. This ...

An integrated deep learning model for early and multi-class diagnosis of Alzheimer's disease from MRI scans.

Scientific reports
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that severely affects memory, behavior, and cognitive function. Early and accurate diagnosis is crucial for effective intervention, yet detecting subtle changes in the early stages ...

Deep normative modelling reveals insights into early-stage Alzheimer's disease using multi-modal neuroimaging data.

Alzheimer's research & therapy
BACKGROUND: Exploring the early stages of Alzheimer's disease (AD) is crucial for timely intervention to help manage symptoms and set expectations for affected individuals and their families. However, the study of the early stages of AD involves anal...

Advancing Remote Monitoring for Patients With Alzheimer Disease and Related Dementias: Systematic Review.

JMIR aging
BACKGROUND: Using remote monitoring technology in the context of Alzheimer disease (AD) care presents exciting new opportunities to lessen caregiver stress and improve patient care quality. The application of wearables, environmental sensors, and sma...

Discovery, Biological Evaluation and Binding Mode Investigation of Novel Butyrylcholinesterase Inhibitors Through Hybrid Virtual Screening.

Molecules (Basel, Switzerland)
Butyrylcholinesterase (BChE), plays a critical role in alleviating the symptoms of Alzheimer's disease (AD) by regulating acetylcholine levels, emerging as an attractive target for AD treatment. This study employed a quantitative structure-activity r...

Cross study transcriptomic investigation of Alzheimer's brain tissue discoveries and limitations.

Scientific reports
Developing effective treatments for Alzheimer's disease (AD) likely requires a deep understanding of molecular mechanisms. Integration of transcriptomic datasets and developing innovative computational analyses may yield novel molecular targets with ...