Developing an Artificial Intelligence System to Detect Cognitive Impairment

Alzheimer's disease dementia (AD) is a debilitating and prevalent neurodegenerative disease in older adults globally. Cognitive impairment, a hallmark of AD, is assessed through verbal tests that require high specialization, and while accepted as screening tools for AD, general practitioners seldom use them. AD can be diagnosed with expensive, invasive neuroimaging and blood tests, but these are usually conducted when cognitive functioning is already severely impaired. Thus, finding a novel, non-invasive tool to detect and differentiate mild cognitive impairment (MCI) and AD is a prime public health interest. Self-figure drawings (a projective tool in which individuals are asked to draw a picture of themselves), are easy to administer and have been shown to differentiate between healthy and cognitively impaired individuals, including AD. Convolutional Neural Network (CNN) (a type of deep neural network, applied to analyze visual imagery) has advanced to assess health conditions using art products. Therefore, the proposed study suggests utilizing CNN-based methods to develop and test an application tailored to differentiate between drawings of individuals with MCI, AD, and healthy controls (HC) using 4,000 self-figure drawings. This

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Key information

Conditions

Alzheimer Disease Brain Diseases Central Nervous System Diseases Cognition Disorders Cognitive Dysfunction Dementia Healthy Aging Mental Disorders Mild Cognitive Impairment Nervous System Diseases Neurocognitive Disorders Neurodegenerative Diseases Tauopathies

Age range

60 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

University of Haifa

Haifa, Israel

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Adults aged 60 and above with subtle signs of risk of future cognitive decline, residing in the community or in nursing homes with a minimum of 10 years of education.

Exclusion criteria

Current or past psychiatric illness, the presence of congenital/organic cognitive condition, severe visual or motor impairment, and terminal illness (to avoid the effect of comorbidities).

Treatment and study plan

Primary outcomes

Cognition

Time frame: One day

The Montreal Cognitive Assessment (MoCA) is a 10-minute paper-based test that aims to detect MCI in older patients with symptomatology, suggesting impaired cognition. The MoCA is composed of 12 tasks to detect short-term memory, visuospatial ability, executive functioning, phonemic fluency, abstraction, attention, concentration, working memory, language, and orientation.
Cognition for adults diagnosed with Alzheimer's disease

Time frame: One day

The Self-reported Cognitive Difficulties (CDS)75 is a 39-item questionnaire that requires participants or their caregivers in case of AD to rate how often they currently experience cognitive difficulties in everyday life using a 5-point scale (0 -"never" to 4 -"very often").
Self-figure drawing -Cognition

Time frame: One day

Self-figure drawing. Participants will be asked to draw themselves using a pencil on an A4-sized sheet of paper.

Sponsors and collaborators

Lead sponsor

University of Haifa

Other

Collaborators

Technion, Israel Institute of Technology

Registry information

Official study title

Developing an Artificial Intelligence System to Detect Mild Cognitive Impairment and Alzheimer's Disease Dementia Through Self-Figure Drawing: An Innovative Approach

Important dates

Study start: 2023
Primary completion: 2025
Study completion: 2026
First posted: Apr 3, 2023
Registry last updated: May 4, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

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