ArticleNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2026
Clinical validation of a voice-based AI tool for screening cognitive impairment: a prospective multicenter study.
Article in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundEarly, scalable screening for cognitive impairment is needed beyond traditional paper-and-pencil tools.
objectiveTo evaluate the diagnostic accuracy and usability of SPICK, a Korean-language, voice-based cognitive screener.
methodsIn a prospective multicenter validation study (ITT N = 399), the reference diagnosis cognitively impaired (mild cognitive impairment [MCI] or Alzheimer's dementia [AD]) or cognitively unimpaired (CU) was determined independently by board-certified neurologists; SPICK provided the index test result. The primary endpoint was SPICK sensitivity and specificity versus prespecified thresholds (≥ 80% and ≥ 59%). Secondary endpoints included subgroup performance (MCI vs CU; AD vs CU), accuracy, area under the receiver operating characteristic (ROC) curve [AUC], and System Usability Scale (SUS).
resultsFor cognitive impairment detection, SPICK achieved sensitivity 85.71% (95% confidence interval [CI] 81.46-89.31%) and specificity 74.29% (62.44-83.99%), meeting thresholds; AUC 0.800 and accuracy 83.71%. Subgroup analyses showed MCI sensitivity 79.64% (72.73-85.47%) and specificity 74.29% (62.44-83.99%), and AD sensitivity 91.98% (86.67-95.66%) and specificity 74.29% (62.44-83.99%). Among 395 participants with usability data, mean SUS was 67.32 (SD 19.10; median 70.0).
conclusionSPICK demonstrated clinically meaningful accuracy with acceptable usability, supporting its potential as an automated, voice-based screening tool for diverse clinical settings.
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