Dementia

NeuroXVocal: Detection and Explanation of Alzheimer's Disease through Non-invasive Analysis of Picture-prompted Speech

The early diagnosis of Alzheimer's Disease (AD) through non invasive methods remains a significant healthcare challenge. We present NeuroXVocal, a novel dual-component system that not only classifies but also explains potential AD cases through speech analysis. The classification component (Neuro) processes three distinct data streams: acoustic features capturing speech patterns and voice charac...

Analyzing Patient Daily Movement Behavior Dynamics Using Two-Stage Encoding Model

In the analysis of remote healthcare monitoring data, time series representation learning offers substantial value in uncovering deeper patterns of patient behavior, especially given the fine temporal granularity of the data. In this study, we focus on a dataset of home activity records from people living with Dementia. We propose a two-stage self-supervised learning approach. The first stage in...

Evaluating GPT's Capability in Identifying Stages of Cognitive Impairment from Electronic Health Data

Identifying cognitive impairment within electronic health records (EHRs) is crucial not only for timely diagnoses but also for facilitating research...

Lifespan tree of brain anatomy: diagnostic values for motor and cognitive neurodegenerative diseases

The differential diagnosis of neurodegenerative diseases, characterized by overlapping symptoms, may be challenging. Brain imaging coupled with arti...

Two-Stage Representation Learning for Analyzing Movement Behavior Dynamics in People Living with Dementia

In remote healthcare monitoring, time series representation learning reveals critical patient behavior patterns from high-frequency data. This study...

Choroidal image analysis for OCT image sequences with applications in systemic health

The choroid, a highly vascular layer behind the retina, is an extension of the central nervous system and has parallels with the renal cortex, with ...

Can ChatGPT Diagnose Alzheimer's Disease?

Can ChatGPT diagnose Alzheimer's Disease (AD)? AD is a devastating neurodegenerative condition that affects approximately 1 in 9 individuals aged 65...

Image-Based Alzheimer's Disease Detection Using Pretrained Convolutional Neural Network Models

Alzheimer's disease is an untreatable, progressive brain disorder that slowly robs people of their memory, thinking abilities, and ultimately their ...

Explainable and externally validated machine learning for neuropsychiatric diagnosis via electrocardiograms

Electrocardiogram (ECG) analysis has emerged as a promising tool for identifying physiological changes associated with neuropsychiatric conditions. ...

DECT: Harnessing LLM-assisted Fine-Grained Linguistic Knowledge and Label-Switched and Label-Preserved Data Generation for Diagnosis of Alzheimer's Disease

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease affecting 50 million people worldwide. Low-cost, accurate identification of ke...

Leveraging Geolocation in Clinical Records to Improve Alzheimer's Disease Diagnosis Using DMV Framework

Alzheimer's Disease (AD) early detection is critical for enabling timely intervention and improving patient outcomes. This paper presents a DMV fram...

Unravelling Causal Genetic Biomarkers of Alzheimer's Disease via Neuron to Gene-token Backtracking in Neural Architecture: A Groundbreaking Reverse-Gene-Finder Approach

Alzheimer's Disease (AD) affects over 55 million people globally, yet the key genetic contributors remain poorly understood. Leveraging recent advan...

Diagnosis of Alzheimer's disease using FusionNet with improved secretary bird optimization algorithm for optimal MK-SVM based on imaging genetic data.

Alzheimer's disease is an irreversible central neurodegenerative disease, and early diagnosis of Alzheimer's disease is beneficial for its prevention ...

Dementia Classification Using Acoustic Speech and Feature Selection

Dementia is a general term for a group of syndromes that affect cognitive functions such as memory, thinking, reasoning, and the ability to perform ...

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis

Functional MRI (fMRI) and single-cell transcriptomics are pivotal in Alzheimer's disease (AD) research, each providing unique insights into neural f...

VisTA: Vision-Text Alignment Model with Contrastive Learning using Multimodal Data for Evidence-Driven, Reliable, and Explainable Alzheimer's Disease Diagnosis

Objective: Assessing Alzheimer's disease (AD) using high-dimensional radiology images is clinically important but challenging. Although Artificial I...

Sleep efficiency in community-dwelling persons living with dementia: exploratory analysis using machine learning.

STUDY OBJECTIVES: Sleep disturbances lead to negative health outcomes and caregiver burden, particularly in community settings. This study aimed to in...

Beyond electronic health record data: leveraging natural language processing and machine learning to uncover cognitive insights from patient-nurse verbal communications.

BACKGROUND: Mild cognitive impairment and early-stage dementia significantly impact healthcare utilization and costs, yet more than half of affected p...

Evaluating Spoken Language as a Biomarker for Automated Screening of Cognitive Impairment

Timely and accurate assessment of cognitive impairment is a major unmet need in populations at risk. Alterations in speech and language can be early...

Integrating Reinforcement Learning and AI Agents for Adaptive Robotic Interaction and Assistance in Dementia Care

This study explores a novel approach to advancing dementia care by integrating socially assistive robotics, reinforcement learning (RL), large langu...