Classification of Alzheimer's disease stages by analyzing prefrontal near-infrared signals during olfactory stimulation with machine learning
J. G. Kim, J. W. Kim
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AbstractAlzheimer's disease (AD) is known as a disease caused by the accumulation of beta-amyloid or tau protein in neurons, blocking signal transmission and causing death. Since there is no cure for this disease, early detection is an important aspect of AD (Rasmussen J et al., 2019). It has been reported that the olfactory function decreases earlier than the cognitive dysfunction in AD patients. (Roberts RO et al., 2015). We have previously reported that the brain hemodynamic signals measured by functional near-infrared spectroscopy during olfactory stimulation could classify the stage of Alzheimer's disease based on a statistical model using 98 patients (55 normal, 26 mild cognitive impairments, 16 dementia) (Kim J et al., 2022). In this study, we recruited additional 34 subjects and applied machine learning to find its potential in AD screening.Keywords: cognitive impairment, Alzheimer’s disease, fNIRS, mild cognitive impairment, machine learning
J. G. Kim, J. W. Kim (2022). Classification of Alzheimer's disease stages by analyzing prefrontal near-infrared signals during olfactory stimulation with machine learning. Gerontechnology, 21(s),3-3
https://doi.org/10.4017/gt.2022.21.s.821.3.sp3