Insights From the Eyes: A Systematic Review and Meta-Analysis of the Intersection Between Eye-Tracking and Artificial Intelligence in Dementia Publisher



Norouzi M¹ ; Kafieh R² ; Chazot P³ ; Smith DT⁴ ; Amini Z⁵ Show Affiliations
Source: Aging and Mental Health Published:2025

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. © 2025 Informa UK Limited, trading as Taylor & Francis Group.