Journal: Alzheimer's & Dementia : Diagnosis, Assessment & Disease Monitoring

Article Title: Computerized cognitive practice effects in relation to amyloid and tau in preclinical Alzheimer's disease: Results from a multi‐site cohort

doi: 10.1002/dad2.12414

Figure Lengend Snippet: C3 practice effects. (A) C3 score changes from initial to repeat assessments. Colored lines depict scores for an individual subject. Black lines indicate the mean score change for those who declined from initial to repeat assessments ( n = 1341) and for those who improved from initial to repeat assessments ( n = 2800). (B) Relation between initial performance and practice effects after controlling for age, sex, education, race, and ethnicity. (C) Association between tau and C3 practice effects. Participants were first stratified into 5 quartiles based on initial C3 performance. By examining stratified groups (i.e., restricting the range of baseline values), we removed the negative association between initial performance and practice effects. Associations between tau and C3 practice effects for each stratified group after adjusting for demographic variables were examined (left column). Despite the reduced power in the stratified groups, the beta weights are similar to those calculated from all participants after adjusting for demographics and initial performance (right column). A−, normal amyloid; A+, abnormal amyloid; BPSO, behavioral pattern separation task‐object; C3, computerized cognitive composite; FNAME, Face Name Associative Memory Examination; OCL, One Card Learning.

Article Snippet: The C3 combines three memory‐based scores: (1) Behavioral Pattern Separation Task‐Object (BPSO) lure discrimination index, (2) Face Name Associative Memory Exam (FNAME) accuracy on the face‐name matching task, and (3) One Card Learning (OCL) accuracy from the CogState Brief Battery (Table ).

Techniques:

Journal: Alzheimer's & Dementia : Diagnosis, Assessment & Disease Monitoring

Article Title: Computerized cognitive practice effects in relation to amyloid and tau in preclinical Alzheimer's disease: Results from a multi‐site cohort

doi: 10.1002/dad2.12414

Figure Lengend Snippet: Beta weights (standard errors) and p ‐values for demographic variables predicting (A) initial performance and (B) practice effects, as well as (C) the association between demographic variables and initial performance in predicting practice effects.

Article Snippet: The C3 combines three memory‐based scores: (1) Behavioral Pattern Separation Task‐Object (BPSO) lure discrimination index, (2) Face Name Associative Memory Exam (FNAME) accuracy on the face‐name matching task, and (3) One Card Learning (OCL) accuracy from the CogState Brief Battery (Table ).

Techniques:

Journal: Alzheimer's & Dementia : Diagnosis, Assessment & Disease Monitoring

Article Title: Computerized cognitive practice effects in relation to amyloid and tau in preclinical Alzheimer's disease: Results from a multi‐site cohort

doi: 10.1002/dad2.12414

Figure Lengend Snippet: Beta weights (Standard Errors) and p ‐values for amyloid status and tau predicting initial computerized cognitive composite performance, computerized cognitive composite practice effects, and computerized cognitive composite practice effects controlling for initial performance. All models additionally control for age, sex, education, race, and ethnicity.

Article Snippet: The C3 combines three memory‐based scores: (1) Behavioral Pattern Separation Task‐Object (BPSO) lure discrimination index, (2) Face Name Associative Memory Exam (FNAME) accuracy on the face‐name matching task, and (3) One Card Learning (OCL) accuracy from the CogState Brief Battery (Table ).

Techniques: Control

Journal: Alzheimer's & Dementia : Diagnosis, Assessment & Disease Monitoring

Article Title: Computerized cognitive practice effects in relation to amyloid and tau in preclinical Alzheimer's disease: Results from a multi‐site cohort

doi: 10.1002/dad2.12414

Figure Lengend Snippet: Initial C3 score performance and its association with amyloid and tau. (A) Initial C3 performance was higher in amyloid negative (A−, pink) than amyloid positive (A+, green) individuals. (B) Greater tau burden was associated with worse initial C3 performance in A+ individuals. C3 scores shown here were adjusted for age, sex, education, race, and ethnicity for visualization purposes. BPSO, behavioral pattern separation task‐object; C3, computerized cognitive composite; FNAME, Face Name Associative Memory Examination; OCL, One Card Learning.

Article Snippet: The C3 combines three memory‐based scores: (1) Behavioral Pattern Separation Task‐Object (BPSO) lure discrimination index, (2) Face Name Associative Memory Exam (FNAME) accuracy on the face‐name matching task, and (3) One Card Learning (OCL) accuracy from the CogState Brief Battery (Table ).

Techniques:

Journal: Computational and Mathematical Methods in Medicine

Article Title: Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

doi: 10.1155/2016/3572705

Figure Lengend Snippet: The psudocode the BPSO/SVM.

Article Snippet: BQPSO/SVM approach was implemented on MATLAB, along with BPSO/SVM and GA/SVM.

Techniques:

Journal: Computational and Mathematical Methods in Medicine

Article Title: Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

doi: 10.1155/2016/3572705

Figure Lengend Snippet: Comparison of accuracy with the proposed algorithm, BPSO/SVM, and GA/SVM.

Article Snippet: BQPSO/SVM approach was implemented on MATLAB, along with BPSO/SVM and GA/SVM.

Techniques:

Journal: Computational and Mathematical Methods in Medicine

Article Title: Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

doi: 10.1155/2016/3572705

Figure Lengend Snippet: The average number of genes selected by BQPSO/SVM, BPSO/SVM, and GA/SVM, respectively.

Article Snippet: BQPSO/SVM approach was implemented on MATLAB, along with BPSO/SVM and GA/SVM.

Techniques:

Journal: Computational and Mathematical Methods in Medicine

Article Title: Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

doi: 10.1155/2016/3572705

Figure Lengend Snippet: Comparison in terms of statistical results of BQPSO/SVM, BPSO/SVM, and GA/SVM.

Article Snippet: BQPSO/SVM approach was implemented on MATLAB, along with BPSO/SVM and GA/SVM.

Techniques: