“School of Cognitive Sciences”
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Paper IPM / Cognitive Sciences / 16591 |
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INTRODUCTION Early detection and monitoring of mild cognitive impairment (MCI) and Alzheimer�??s Disease (AD) patients are key to tackling dementia and providing benefits to patients, caregivers, healthcare providers and society. We developed the Integrated Cognitive Assessment (ICA); a 5-minute, language independent computerised cognitive test that employs an Artificial Intelligence (AI) model to improve its accuracy in detecting cognitive impairment. In this study, we aimed to evaluate the generalisability of the ICA in detecting cognitive impairment in MCI and mild AD patients.
METHODS We studied the ICA in a total of 230 participants. 95 healthy volunteers, 80 MCI, and 55 participants with mild AD completed the ICA, the Montreal Cognitive Assessment (MoCA) and Addenbrooke�??s Cognitive Examination (ACE) cognitive tests.
RESULTS The ICA demonstrated convergent validity with MoCA (Pearson r = 0.58, p<0.0001) and ACE (r = 0.62, p<0.0001). The ICA AI model was able to detect cognitive impairment with an AUC of 81
DISCUSSION The ICA can support clinicians by aiding accurate diagnosis of MCI and AD and is appropriate for large-scale screening of cognitive impairment. The ICA is unbiased by differences in language, culture and education.
Competing Interest Statement
SMKR serves as the Chief Scientific Officer at Cognetivity Ltd. CK serves as the Chief Medical Officer at Cognetivity Ltd and Principal Investigator on NIHR and Industry-funded clinical trials. HM is Data Science Lead at Cognetivity Ltd. DA has received research support and/or honoraria from Astra-Zeneca, H. Lundbeck, Novartis Pharmaceuticals, Biogen, and GE Health, and served as paid consultant for H. Lundbeck, Eisai, Heptares, and Mentis Cura. Other authors declared no potential conflicts of interest.
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