The primary objective of the study is to evaluate whether a set of algorithms analysing acoustic and linguistic patterns of speech can detect amyloid-specific cognitive impairment in early stage Alzheimer's disease, based on archival spoken or written language samples, as measured by the area under the curve (AUC) of the receiver operating characteristic curve of the binary classifier distinguishing between amyloid positive and amyloid negative arms. Secondary objectives include (1) evaluating how many years before diagnosis of Mild Cognitive Impairment (MCI) such algorithms work, as measured on binary classifier performance of the classifiers trained to classify MCI vs cognitively normal (CN) arms using archival material from the following time bins before MCI diagnosis: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years; (2) evaluating at what age such algorithms can detect later amyloid positivity, as measured on binary classifier performance of the classifiers trained to classify amyloid positive vs amyloid negative arms using archival material from the following age bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old.
Study Type
OBSERVATIONAL
Enrollment
40
Syrentis Clinical Research
Santa Ana, California, United States
RECRUITINGThe area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms.
Using archival spoken or written language samples as input.
Time frame: Up to 85 years
The sensitivity of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms using archival spoken or written language samples as input.
Time frame: Up to 85 years
The specificity of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms using archival spoken or written language samples as input.
Time frame: Up to 85 years
The Cohen's kappa of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms using archival spoken or written language samples as input.
Time frame: Up to 85 years
The AUC of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.
Using archival spoken or written language samples as input in the following bins: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years before MCI diagnosis.
Time frame: Up to 85 years
The sensitivity of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.
Using archival spoken or written language samples as input in the following bins: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years before MCI diagnosis.
Time frame: Up to 85 years
The specificity of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.
Using archival spoken or written language samples as input in the following bins: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years before MCI diagnosis.
Time frame: Up to 85 years
The Cohen's kappa of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.
Using archival spoken or written language samples as input in the following bins: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years before MCI diagnosis.
Time frame: Up to 85 years
The AUC of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms.
Using archival spoken or written language samples as input in the following bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old.
Time frame: Up to 85 years
The sensitivity of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms.
Using archival spoken or written language samples as input in the following bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old.
Time frame: Up to 85 years
The specificity of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms.
Using archival spoken or written language samples as input in the following bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old.
Time frame: Up to 85 years
The Cohen's kappa of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms.
Using archival spoken or written language samples as input in the following bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old.
Time frame: Up to 85 years
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