| 摘要 |
Disclosed are a device and a method for predicting the incidence rate of the Alzheimer′s disease by utilizing a beta-amyloid concentration, a p-FET measurement value, and a PMT measurement value as input data, extracting the feature values of the input data, and applying the feature values to a pattern recognizing algorithm. The device comprises: a feature extracting part for extracting the feature values through the recognition of a pattern by comparing a beta-amyloid concentration value contained in a sample to be measured, a photosensitive field-effect transistor measurement value, and a photo multiplier tube measurement value, which are inputted from the outside, with pre-stored initial values; and an incidence rate predicting part for predicting the incidence rate of the Alzheimer′s disease based on the extracted feature values. The photosensitive field-effect transistor measurement value is obtained by measuring the photoelectric current of light emitted by exciting light while the sample in which the beta-amyloid and fluorescent substances are combined is fixed in the sensing section of a photosensitive field-effect transistor, and the photo multiplier tube measurement value is obtained by measuring the number of photons in the light emitted by exciting the light to the same sample used in the measurement of the photoelectric current. |
