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ABSTRACT: Background
Accurate diagnosis and assessment of mild cognitive impairment (MCI) are essential. The efficacy of saccades in the detection of MCI lacks validation through large-scale clinical trials.Methods
All eligible participants underwent saccadic assessment in four tasks and a cognitive assessment. MCI diagnoses were made on the basis of clinical indicators and MRI by experienced physicians. The physicians were blinded to the saccade experiments, and the operators of the saccade experiments were blind to the diagnosis of physicians. The classification models based on machine learning were constructed for assessing the diagnostic accuracy of MCI based on saccadic parameters.Results
Of the 559 residents who consented to participate, 383 (153 with MCI and 230 contro
SUBMITTER: Sha L
PROVIDER: S-EPMC12832980 | biostudies-literature | 2026 Jan
REPOSITORIES: biostudies-literature