Construction of a prediction model for Alzheimer’s disease using an AI-driven eye-tracking task on mobile devices
This novel AI-driven eye-tracking technology has the potential to reliably identify differences in eye-movement abnormalities in AD. The model shows excellent diagnostic performance in identifying AD based on the current data collected. The use of mobile devices makes it accessible for AD patients to complete tasks in primary clinical settings or follow up at home.
Authors
- Jiaxin Yan
- Zhilan Tu (ORCID: https://orcid.org/0000-0001-9542-7717)
- Jianfeng Ye (ORCID: https://orcid.org/0000-0001-8597-037X)
- Qinjie Li
- Hao Lv (ORCID: https://orcid.org/0000-0003-3090-8653)
- Qihao Guo (ORCID: https://orcid.org/0000-0001-5079-8047)
- Xiaochen Zhang (ORCID: https://orcid.org/0000-0002-7154-5337)
- Yunxia Li (ORCID: https://orcid.org/0000-0002-0626-2584)
Institutions
- Shanghai University (CN)
- Tongji University (CN)
- Shanghai Jiao Tong University (CN)
- Fudan University (CN)
- Pudong Medical Center (CN)
- Shanghai Sixth People's Hospital (CN)
- Tongji Hospital (CN)
Publication Details
- Journal
- Aging Clinical and Experimental Research
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1007/s40520-024-02882-9
- Citations
- 4
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 1.54
Funders
- Shanghai Municipal Health Commission
- Shanghai Jiao Tong University
- Shanghai Hospital Development Center