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For: Readman MR, Polden M, Gibbs MC, Wareing L, Crawford TJ. The Potential of Naturalistic Eye Movement Tasks in the Diagnosis of Alzheimer's Disease: A Review. Brain Sci 2021;11:1503. [PMID: 34827502 DOI: 10.3390/brainsci11111503] [Cited by in Crossref: 2] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Öhman F, Berron D, Papp KV, Kern S, Skoog J, Hadarsson Bodin T, Zettergren A, Skoog I, Schöll M. Unsupervised mobile app-based cognitive testing in a population-based study of older adults born 1944. Front Digit Health 2022;4. [DOI: 10.3389/fdgth.2022.933265] [Reference Citation Analysis]
2 Lehtola J, Kärkkäinen V, Andberg S, Hannonen S, Rusanen M, Saari T, Korhonen V, Hokkanen L, Hallikainen M, Hänninen T, Kaarniranta K, Bednarik R, Leinonen V, Koivisto AM. Computer-based Eye-tracking Analysis of King-Devick Test Differentiates Persons With Idiopathic Normal Pressure Hydrocephalus From Cognitively Unimpaired. Alzheimer Disease & Associated Disorders 2022;Publish Ahead of Print. [DOI: 10.1097/wad.0000000000000527] [Reference Citation Analysis]
3 Kim KW, Wang Q, Koo SH, Shin BS. A single-center, randomized, parallel design study to evaluate the efficacy of donepezil in improving visuospatial abilities in patients with mild cognitive impairment using eye-tracker: the COG-EYE study protocol for a phase II trial. Trials 2022;23:813. [PMID: 36167553 DOI: 10.1186/s13063-022-06781-0] [Reference Citation Analysis]
4 Sun J, Liu Y, Wu H, Jing P, Ji Y. A novel deep learning approach for diagnosing Alzheimer's disease based on eye-tracking data. Front Hum Neurosci 2022;16:972773. [DOI: 10.3389/fnhum.2022.972773] [Reference Citation Analysis]