Alzheimer's Disease

EEG-based neurodegenerative disease diagnosis: comparative analysis of conventional methods and deep learning models.

In the context of lifestyle changes, stress and other environmental factors have resulted in the sudden hike in dementia globally. This necessitates investigations with respect to every horizon of the due cause for it; further on, the diagnosis and treatments can be advanced with the aid of technology. This work attempts to conduct one such investigation on dementia diagnosis based on EEG signals....

Artificial intelligence-driven natural language processing for identifying linguistic patterns in Alzheimer's disease and mild cognitive impairment: A study of lexical, syntactic, and cohesive features of speech through picture description tasks.

BackgroundLanguage deficits often occur early in the neurodegenerative process, yet traditional methods frequently fail to detect subtle changes. Natural language processing (NLP) offers a novel approach to identifying linguistic patterns associated with cognitive impairment.ObjectiveWe aimed to analyze linguistic features that differentiate cognitively unimpaired (CU), mild cognitive impairment (...

Enhancing Neurodegenerative Disease Diagnosis Through Confidence-Driven Dynamic Spatio-Temporal Convolutional Network.

Dynamic brain networks are more effective than static networks in characterizing the evolving patterns of brain functional connectivity, making them a...

AD-AutoGPT: An autonomous GPT for Alzheimer's disease infodemiology.

In this pioneering study, inspired by AutoGPT, the state-of-the-art open-source application based on the GPT-4 large language model, we develop a nove...

New Targets for Imaging in Nuclear Medicine.

Nuclear medicine is rapidly evolving with new molecular imaging targets and advanced computational tools that promise to enhance diagnostic precision ...

AI-driven early diagnosis of specific mental disorders: a comprehensive study.

One of the areas where artificial intelligence (AI) technologies are used is the detection and diagnosis of mental disorders. AI approaches, including...

Systematic Identification of Caregivers of Patients Living With Dementia in the Electronic Health Record: Known Contacts and Natural Language Processing Cohort Study.

BACKGROUND: Systemically identifying caregivers in the electronic health record (EHR) is a critical step for delivering patient-centered care, enhanci...

Predicting and Evaluating Cognitive Status in Aging Populations Using Decision Tree Models.

To improve the identification of cognitive impairment by distinguishing normal cognition (NC), mild cognitive impairment (MCI), and Alzheimer's disea...

Use of posterior probabilities from a long short-term memory network for characterizing dance behavior with multiple accelerometers.

BackgroundDancing may be protective for cognitive health among adults with mild cognitive impairment, Alzheimer's disease or dementia; however, additi...

Cognitive impairment screening strategy to reduce the burden of Alzheimer's disease in Shanghai: A system dynamics approach.

BACKGROUND: Population aging increases the economic burden of Alzheimer's disease (AD). Early screening for mild cognitive impairment (MCI) has the po...

Ensemble Learning-Based Alzheimer's Disease Classification Using Electroencephalogram Signals and Clock Drawing Test Images.

Ensemble learning (EL), a machine learning technique that combines the results of multiple learning algorithms to obtain predicted values, aims to ach...

Assessing the Content of Goals of Care Documentation for Hospitalized Patients With Alzheimer's Disease and Related Dementias.

BACKGROUND: Goals of care (GOC) conversations are an evidence-based practice that help clarify and align patient values and preferences for medical ca...

Modality-Aware Discriminative Fusion Network for Integrated Analysis of Brain Imaging Genomics.

Mild cognitive impairment (MCI) represents an early stage of Alzheimer's disease (AD), characterized by subtle clinical symptoms that pose challenges ...

How Can Anomalous-Diffusion Neural Networks Under Connectomics Generate Optimized Spatiotemporal Dynamics.

Spatiotemporal dynamics in the brain have been recognized as strongly related to the formation of perceived and cognitive diseases, such as delusions ...

The Impact of Telepresence Robots on Family Caregivers and Residents in Long-Term Care.

Telepresence robots can enhance social connection and support person-centered care in long-term care (LTC) homes. This study evaluates their impact in...

Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study.

BACKGROUND: Cognitive impairment, indicative of Alzheimer disease and other forms of dementia, significantly deteriorates the quality of life of older...

Alzheimer's disease knowledge graph enhances knowledge discovery and disease prediction.

OBJECTIVE: To construct an Alzheimer's Disease Knowledge Graph (ADKG) by extracting and integrating relationships among Alzheimer's disease (AD), gene...

AI in Home Care-Evaluation of Large Language Models for Future Training of Informal Caregivers: Observational Comparative Case Study.

BACKGROUND: The aging population presents an accomplishment for society but also poses significant challenges for governments, health care systems, an...

A novel diagnosis method utilizing MDBO-SVM and imaging genetics for Alzheimer's disease.

Alzheimer's disease (AD) is the most common neurodegenerative disorder, yet its underlying mechanisms remain elusive. Early and accurate diagnosis is ...

Therapeutic potential of enzymes, neurosteroids, and synthetic steroids in neurodegenerative disorders: A critical review.

Neurodegenerative disorders present a significant challenge to healthcare systems, mainly due to the limited availability of effective treatment optio...