AIMC Topic: Cognitive Dysfunction

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Retinal image-based deep learning for mild cognitive impairment detection in coronary artery disease population.

Heart (British Cardiac Society)
BACKGROUND: Coronary artery disease (CAD) is linked to an increased risk of mild cognitive impairment (MCI). Effective and convenient screening methods for identifying MCI from the CAD population are still lacking. This study aims to develop a deep l...

A Conversational Robot for Cognitively Impaired Older People Who Live Alone: An Exploratory Feasibility Study.

Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
BACKGROUND: Social isolation and loneliness are significant risk factors for poor mental health in older adults, particularly those living alone with cognitive impairment. Socially assistive robots (SARs) offer a promising approach to enhance social ...

Fractal analysis for cognitive impairment classification in DAVF using machine learning.

Biomedical physics & engineering express
. Intracranial dural arteriovenous fistula (DAVF) is an acquired vascular condition involving abnormal connections between dural arteries and veins without intervening capillary beds. Cognitive impairment is a common symptom in DAVFs, often linked to...

Machine learning diagnosis of cognitive impairment and dementia in harmonized older adult cohorts.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Clinical diagnosis (normal cognition, mild cognitive impairment [MCI], dementia) is critical for understanding cognitive impairment and dementia but can be resource intensive and subject to inconsistencies due to complex clinical judgme...

Brain age prediction from MRI scans in neurodegenerative diseases.

Current opinion in neurology
PURPOSE OF REVIEW: This review explores the use of brain age estimation from MRI scans as a biomarker of brain health. With disorders like Alzheimer's and Parkinson's increasing globally, there is an urgent need for early detection tools that can ide...

Exploring oculomotor challenges in amyotrophic lateral sclerosis: a comprehensive review.

Amyotrophic lateral sclerosis & frontotemporal degeneration
Traditionally understood as a motor neuron disease, amyotrophic lateral sclerosis (ALS) is now recognized to involve broader neurodegenerative processes, including the oculomotor system. This narrative review summarizes current evidence on oculomotor...

Artificial Intelligence-Assisted Hippocampal Segmentation and Its Diagnostic Value for Alzheimer's Disease: A Meta-analysis.

Academic radiology
BACKGROUND: Hippocampal atrophy is a key marker of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Diverse artificial intelligence (AI) architectures for automated hippocampal segmentation have been increasingly reported in neuroimaging...

Role of Brain Age Gap as a Mediator in the Relationship Between Cognitive Impairment Risk Factors and Cognition.

Neurology
BACKGROUND AND OBJECTIVES: Cerebrovascular disease (CeVD) and cognitive impairment risk factors contribute to cognitive decline, but the role of brain age gap (BAG) in mediating this relationship remains unclear, especially in Southeast Asian populat...

Modeling the Determinants of Subjective Well-Being in Schizophrenia.

Schizophrenia bulletin
BACKGROUND: The ultimate goal of successful schizophrenia treatment is not just to alleviate psychotic symptoms, but also to reduce distress and achieve subjective well-being (SWB). We aimed to identify the determinants of SWB and their interrelation...

Predicting cognitive function among Chinese community-dwelling older adults: A supervised machine learning approach.

Preventive medicine
OBJECTIVE: Identifying cognitive impairment early enough could support timely intervention of cognitive impairment and facilitate successful cognitive aging. We aimed to build more precise prediction models for cognitive function using less variable ...