Dementia

NeuroAIreh@b: an artificial intelligence-based methodology for personalized and adaptive neurorehabilitation.

Cognitive impairments are a prevalent consequence of acquired brain injury, dementia, and age-relate...

Harnessing Transfer Learning for Dementia Prediction: Leveraging Sex-Different Mild Cognitive Impairment Prognosis.

This paper presents a machine learning-based prediction for dementia, leveraging transfer learning t...

Estimating dementia risk in an African American population using the DCTclock.

The prevalence of Alzheimer's disease (AD) and related dementias (ADRD) is increasing. African Ameri...

Deep insights into MCI diagnosis: A comparative deep learning analysis of EEG time series.

BACKGROUND: Individuals in the early stages of Alzheimer's Disease (AD) are typically diagnosed with...

Determination of Alzheimer's disease based on morphology and atrophy using machine learning combined with automated segmentation.

BACKGROUND: To evaluate the degree of cerebral atrophy for Alzheimer's disease (AD), voxel-based mor...

Editorial: Quantitative imaging methods and analysis in Alzheimer's disease assessment.

The ménage à trois of healthcare: the actors in after-AI era under patient consent.

INTRODUCTION: Artificial intelligence has become an increasingly powerful technological instrument i...

Breaking barriers: a statistical and machine learning-based hybrid system for predicting dementia.

Dementia is a condition (a collection of related signs and symptoms) that causes a continuing deter...

Explaining graph convolutional network predictions for clinicians-An explainable AI approach to Alzheimer's disease classification.

INTRODUCTION: Graph-based representations are becoming more common in the medical domain, where each...

Ocular biomarkers of cognitive decline based on deep-learning retinal vessel segmentation.

BACKGROUND: The current literature shows a strong relationship between retinal neuronal and vascular...

Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol.

More than 10 million Europeans show signs of mild cognitive impairment (MCI), a transitional stage b...

Emerging perspectives of synaptic biomarkers in ALS and FTD.

Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Dementia (FTD) are debilitating neurodegenera...

Role of Artificial Intelligence in Multinomial Decisions and Preventative Nutrition in Alzheimer's Disease.

Alzheimer's disease (AD) affects 50 million people worldwide, an increase of 35 million since 2015, ...

Mild cognitive impairment prediction and cognitive score regression in the elderly using EEG topological data analysis and machine learning with awareness assessed in affective reminiscent paradigm.

INTRODUCTION: The main objective of this study is to evaluate working memory and determine EEG bioma...

Enabling Lipidomic Biomarker Studies for Protected Populations by Combining Noninvasive Fingerprint Sampling with MS Analysis and Machine Learning.

Triacylglycerols and wax esters are two lipid classes that have been linked to diseases, including a...

Antioxidant and anticholinesterase properties of and venoms from the Persian Gulf.

The Persian Gulf is home to a diverse range of marine life, including various species of fish, crus...

Modelling phenomenological differences in aetiologically distinct visual hallucinations using deep neural networks.

Visual hallucinations (VHs) are perceptions of objects or events in the absence of the sensory stimu...

Using Generative Artificial Intelligence to Classify Primary Progressive Aphasia from Connected Speech.

Neurodegenerative dementia syndromes, such as Primary Progressive Aphasias (PPA), have traditionally...

Assess Alzheimer's Disease via Plasma Extracellular Vesicle-derived mRNA.

Alzheimer's disease (AD), the most prevalent neurodegenerative disorder globally, has emerged as a s...

Deep learning applications in vascular dementia using neuroimaging.

PURPOSE OF REVIEW: Vascular dementia (VaD) is the second common cause of dementia after Alzheimer's ...

Brain age prediction using combined deep convolutional neural network and multi-layer perceptron algorithms.

The clinical applications of brain age prediction have expanded, particularly in anticipating the on...