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Related papers: Predicting Mild Cognitive Impairment Using Natural…

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Driving is a complex daily activity indicating age and disease related cognitive declines. Therefore, deficits in driving performance compared with ones without mild cognitive impairment (MCI) can reflect changes in cognitive functioning.…

We introduce scenario-based cognitive status identification in older drivers from naturalistic driving videos, leveraging large vision models. In recent times, cognitive decline including Dementia and Mild Cognitive Impairment (MCI), is…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Md Zahid Hasan , Guillermo Basulto-Elias , Jun Ha Chang , Shauna Hallmark , Matthew Rizzo , Anuj Sharma , Soumik Sarkar

INTRODUCTION: Mild cognitive impairment (MCI) is characterized by a decline in cognitive functions beyond typical age and education-related expectations. Since, MCI has been linked to reduced social interactions and increased aimless…

Artificial Intelligence · Computer Science 2024-08-21 Chaitra Hegde , Yashar Kiarashi , Allan I Levey , Amy D Rodriguez , Hyeokhyen Kwon , Gari D Clifford

The aging society urgently requires scalable methods to monitor cognitive decline and identify social and psychological factors indicative of dementia risk in older adults. Our machine learning (ML) models captured facial, acoustic,…

Early detection of Mild Cognitive Impairment (MCI) leads to early interventions to slow the progression from MCI into dementia. Deep Learning (DL) algorithms could help achieve early non-invasive, low-cost detection of MCI. This paper…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Muath Alsuhaibani , Hiroko H. Dodge , Mohammad H. Mahoor

Mild cognitive impairment (MCI) may affect up to 20 % of people over 65 years old. Global incidence of MCI is increasing, and technology is being explored for early intervention. Theories of technology adoption predict that useful and easy…

Human-Computer Interaction · Computer Science 2025-07-03 Snezna B Schmidt , Stephen Isbel , Blooma John , Ram Subramanian , Nathan M DCunha

The global prevalence of dementia is projected to double by 2050, highlighting the urgent need for scalable diagnostic tools. This study utilizes digital cognitive tasks with eye-tracking data correlated with memory processes to distinguish…

Human-Computer Interaction · Computer Science 2025-08-28 Tomás Silva Santos Rocha , Anastasiia Mikhailova , Moreno I. Coco , José Santos-Victor

Mild cognitive impairment (MCI) leading to dementia results in a constellation of psychiatric disorders including depression, mood disorders, schizophrenia and others. With increasing age, mild cognitive impairment leads to increased…

Neurons and Cognition · Quantitative Biology 2023-08-10 Sheng Mai

Purpose: This study investigates whether a machine-learning-based system can predict the rate of cognitive decline in mildly cognitively impaired patients by processing only the clinical and imaging data collected at the initial visit.…

Quantitative Methods · Quantitative Biology 2020-10-07 Sema Candemir , Xuan V. Nguyen , Luciano M. Prevedello , Matthew T. Bigelow , Richard D. White , Barbaros S. Erdal

Delirium represents a significant clinical concern characterized by high morbidity and mortality rates, particularly in patients with mild cognitive impairment (MCI). This study investigates the associated risk factors for delirium by…

Mild Cognitive Impairment (MCI) is an early stage of Alzheimer's disease (AD), a form of neurodegenerative disorder. Early identification of MCI is crucial for delaying its progression through timely interventions. Existing research has…

Audio and Speech Processing · Electrical Eng. & Systems 2024-10-18 Kristin Qi , Jiatong Shi , Caroline Summerour , John A. Batsis , Xiaohui Liang

Early detection of dementia is crucial to devise effective interventions. Comprehensive cognitive tests, while being the most accurate means of diagnosis, are long and tedious, thus limiting their applicability to a large population,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Anusha A. S. , Uma Ranjan , Medha Sharma , Siddharth Dutt

Mild cognitive impairment (MCI) is characterized by subtle changes in cognitive functions, often associated with disruptions in brain connectivity. The present study introduces a novel fine-grained analysis to examine topological…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Ninad Aithal , Debanjali Bhattacharya , Neelam Sinha , Thomas Gregor Issac

The so-called Mild Cognitive Impairment (MCI) or cognitive loss appears in a previous stage before Alzheimer's Disease (AD), but it does not seem sufficiently severe to interfere in independent abilities of daily life, so it usually does…

The paper proposes a novel approach of survival transformers and extreme gradient boosting models in predicting cognitive deterioration in individuals with mild cognitive impairment (MCI) using metabolomics data in the ADNI cohort. By…

Machine Learning · Computer Science 2024-09-25 Henry Musto , Daniel Stamate , Doina Logofatu , Daniel Stahl

Multiple modalities of biomarkers have been proved to be very sensitive in assessing the progression of Alzheimer's disease (AD), and using these modalities and machine learning algorithms, several approaches have been proposed to assist in…

Machine Learning · Statistics 2017-12-05 Chen Fang , Panuwat Janwattanapong , Chunfei Li , Malek Adjouadi

We investigate how hubs of functional brain networks are modified as a result of mild cognitive impairment (MCI), a condition causing a slight but noticeable decline in cognitive abilities, which sometimes precedes the onset of Alzheimer's…

Early detection is crucial for timely intervention aimed at preventing and slowing the progression of neurocognitive disorder (NCD), a common and significant health problem among the aging population. Recent evidence has suggested that…

Computation and Language · Computer Science 2025-06-11 Yuejiao Wang , Xianmin Gong , Xixin Wu , Patrick Wong , Hoi-lam Helene Fung , Man Wai Mak , Helen Meng

This paper presents a deep learning method using Natural Language Processing (NLP) techniques, to distinguish between Mild Cognitive Impairment (MCI) and Normal Cognitive (NC) conditions in older adults. We propose a framework that analyzes…

Computation and Language · Computer Science 2024-02-06 Ali Pourramezan Fard , Mohammad H. Mahoor , Muath Alsuhaibani , Hiroko H. Dodgec

An interpretable machine learning (ML) framework is introduced to enhance the diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) by ensuring robustness of the ML models' interpretations. The dataset used comprises…

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