Developing an Artificial Intelligence System to Detect Cognitive Impairment

NCT05794451 | Completed

• 1 other identifier: ALZAI
• Study Type: observational
• Target: 3,413
• Locations: 1 country
• Sites: 1

Brief Summary

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

Conditions

Alzheimer Disease; Healthy Aging; Mild Cognitive Impairment

Outcome Measures

Primary Outcomes (3)

• Cognition

  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.

  One day

• Cognition for adults diagnosed with Alzheimer's disease

  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").

  One day

• Self-figure drawing -Cognition

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

  One day

Study Arms (3)

Healthy controls

Adults aged 60 and above without cognitive impairment

Mild cognitive impairment

Adults 60 and above with mild cognitive impairment

Alzheimer's disease

Adults diagnosed with Alzheimer's disease

Eligibility Criteria

• Age: 60 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adults aged 60 or above, who live in Israel.

You may qualify if:

• 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.

You may not qualify if:

• 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).

Sponsors & Collaborators

• University of Haifa: lead
• Technion, Israel Institute of Technology: collaborator

Study Sites (1)

University of Haifa

Haifa, Israel

Location

MeSH Terms

Conditions

Alzheimer Disease; Cognitive Dysfunction

Condition Hierarchy (Ancestors)

Dementia; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Tauopathies; Neurodegenerative Diseases; Neurocognitive Disorders; Mental Disorders; Cognition Disorders

Study Officials

• Johanna Czamanski-Cohen, PhD

  University of Haifa

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Senior Lecturer

Study Record Dates

• First Submitted: March 20, 2023
• First Posted: April 3, 2023
• Study Start: March 20, 2023
• Primary Completion: December 31, 2025
• Study Completion: March 31, 2026
• Last Updated: May 4, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

IL (1)