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1 result(s) for "Setiabudi, Eliana"
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ReCOGnAIze app to detect vascular cognitive impairment and mild cognitive impairment
INTRODUCTION Vascular cognitive impairment (VCI), a major cause of cognitive impairment, remains underdiagnosed due to varying non‐amnestic manifestations. It is important to detect VCI at the mild cognitive impairment (MCI) stage or earlier. We aimed to develop and validate ReCOGnAIze, a tablet‐based, gamified, and interpretable app to detect VCI and MCI. METHODS A multi‐phase, cross sectional study in an Asian community cohort with development phase (n = 200) and validation with 235 independent participants having comprehensive neuroimaging and neuropsychological data. RESULTS In differentiating VCI, ReCOGnAIze achieved strong performance (n = 154, AUC = 0.85), identifying digital features: processing speed and response time variability, consistent with known VCI impairments of executive functioning. Additionally, a generalizable ReCOGnAIze composite score distinguished MCI from cognitively healthy (CH) (n = 235, AUC = 0.90), outperforming the Montreal Cognitive Assessment (MoCA) (AUC = 0.70). DISCUSSION ReCOGnAIze is a scalable, explainable artificial intelligence (AI) tool that accurately detects VCI and MCI, with gamified, tablet‐based, interpretable tasks. Highlights Non‐significant differences on Montreal Cognitive Assessment (MoCA) for vascular cognitive impairment (VCI). ReCOGnAIze artificial intelligence (AI) models identify VCI with area under the curve (AUC) of 0.85. ReCOGnAIze games detect mild cognitive impairment (MCI) with AUC of 0.90, outperforming MoCA (AUC = 0.7). Processing speed and response time variability are key VCI markers.