Article

Identifying and Predicting Cognitive Decline Using Multi-Modal Sensor Data and Machine Learning Approach

2025-06-18

Abstract excerpt

<title>Abstract</title> <p> Alzheimer’s Disease (AD) remains a critical global health challenge, with its prevalence expected to rise dramatically by 2050, leading to substantial financial and emotional burdens. Mild Cognitive Impairment (MCI), the prodromal stage of AD, presents a crucial opportunity for early intervention, yet its diagnosis remains difficult due to the overlap with normal aging. Traditional di...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 69803d6a-d7cd-59f9-b136-10ce671997cc
DOI: 10.21203/rs.3.rs-6735622/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Identifying and Predicting Cognitive Decline Using Multi-Modal Sensor Data and Machine Learning ApproachDOI 10.21203/rs.3.rs-6735622/v1Read

Identifying and Predicting Cognitive Decline Using Multi-Modal Sensor Data and Machine Learning ApproachSemantic proximity Read

The Use of Home-Based Behaviours for Detecting Early Dementia:<i>Protocol for the CUBOId Study</i>Semantic proximity Read

A Multi-Agent AI Framework for Predicting Alzheimer’s Disease Trajectory Through Sleep-Dependent Memory Consolidation Biomarkers: A Conceptual ArchitectureSemantic proximity Read

Real-world deployment of remote sleep monitoring technologies reveals distinct patterns associated with cognitive declineSemantic proximity Read

Longitudinal muti-modal data prediction model for mild cognitive impairment by deep survival analysisSemantic proximity Read

AI-enabled digital phenotyping for Alzheimer's disease: a review of multimodal sensor integration and symptom trajectories.Semantic proximity Read

Leveraging Transformer Models to Predict Cognitive Impairment: Accuracy, Efficiency, and InterpretabilitySemantic proximity Read

Contactless longitudinal monitoring of ageing and dementia-related sleep trajectories in the homeSemantic proximity Read

The use of home-based conversations for detecting early dementia: Protocol for the CUBOId TV taskSemantic proximity Read

A Novel Ensemble-Based Machine Learning Algorithm To Predict The Conversion From Mild Cognitive Impairment To Alzheimer’s Disease Using Socio-demographic Characteristics, Clinical Information And Neuropsychological MeasuresSemantic proximity Read

Wearable sensing for quantifying cognitive and balance functions in naturalistic movements of older adults with mild cognitive impairment in therapeutic environmentsSemantic proximity Read

Quantitative longitudinal predictions of Alzheimer’s disease by multi-modal predictive learningSemantic proximity Read