Insights from the eyes: a systematic review and meta-analysis of the intersection between eye-tracking and artificial intelligence in dementia.

Norouzi, Mahdi; Kafieh, Rahele; Chazot, Paul; Smith, Daniel T; Amini, Zahra

Abstract

Objectives
Dementia can change oculomotor behavior, which is detectable through eye-tracking. This study aims to systematically review and conduct a meta-analysis of current literature on the intersection between eye-tracking and artificial intelligence (AI) in detecting dementia.

Method
PubMed, Embase, Scopus, Web of Science, Cochrane, and IEEE databases were searched up to July 2023. All types of studies that utilized eye-tracking and AI to detect dementia and reported the performance metrics, were included. Data on the dementia type, performance, artificial intelligence, and eye-tracking paradigms were extracted. The registered protocol is available online on PROSPERO (ID: CRD42023451996).

Results
Nine studies were finally included with a sample size ranging from 57 to 583 participants. Alzheimer’s disease (AD) was the most common dementia type. Six studies used a machine learning model while three used a deep learning model. Meta-analysis revealed the accuracy, sensitivity, and specificity of using eye-tracking and artificial intelligence in detecting dementia, 88% [95% CI (83%–92%)], 85% [95% CI (75%–93%)], and 86% [95% CI (79%–93%)], respectively.

Conclusion
Eye-tracking coupled with AI revealed promising results in terms of dementia detection. Further studies must incorporate larger sample sizes, standardized guidelines, and include other dementia types.

Citation

Norouzi, M., Kafieh, R., Chazot, P., Smith, D. T., & Amini, Z. (online). Insights from the eyes: a systematic review and meta-analysis of the intersection between eye-tracking and artificial intelligence in dementia. Aging and Mental Health, 1-9. https://doi.org/10.1080/13607863.2025.2464704

• Journal Article Type: Article
• Acceptance Date: Jan 31, 2025
• Online Publication Date: Feb 14, 2025
• Deposit Date: Mar 24, 2025
• Journal: Aging & Mental Health
• Print ISSN: 1360-7863
• Electronic ISSN: 1364-6915
• Publisher: Taylor and Francis Group
• Peer Reviewed: Peer Reviewed
• Pages: 1-9
• DOI: https://doi.org/10.1080/13607863.2025.2464704
• Keywords: Alzheimer’s disease, Eye-tracking, artificial intelligence, dementia, machine learning
• Public URL: https://durham-repository.worktribe.com/output/3560328