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Principal Investigator  
Principal Investigator's Name: Hebert Caballero
Institution: University of Alberta
Department: Neuroscience
Country:
Proposed Analysis: We will analyze cognitive trajectories across the Alzheimer's disease (AD) spectrum. Specifically, we will examine episodic memory trajectories in non-demented, mild cognitive impairment, and AD participants. Genetic (e.g., APOE), neuroimaging (e.g., amyloid PET), CSF (e.g., total tau), and other available biomarkers in ADNI will be used to predict these trajectories using machine learning. Specifically, we will use random forest analysis to detect important biomarker predictors in each of the stages of the AD spectrum.
Additional Investigators  
Investigator's Name: Roger Dixon
Proposed Analysis: We will analyze cognitive trajectories across the Alzheimer's disease (AD) spectrum. Specifically, we will analyze episodic memory trajectories in non-demented, mild cognitive impairment, and AD participants. Genetic (e.g., APOE), neuroimaging (e.g., amyloid PET), CSF (e.g., total tau), and other available biomarkers in ADNI will be used to predict these trajectories using machine learning. Specifically, we will use random forest analysis to detect important biomarker predictors in each of the stages of the AD spectrum.
Investigator's Name: Georgia McFall
Proposed Analysis: We will analyze cognitive trajectories across the Alzheimer's disease (AD) spectrum. Specifically, we will analyze episodic memory trajectories in non-demented, mild cognitive impairment, and AD participants. Genetic (e.g., APOE), neuroimaging (e.g., amyloid PET), CSF (e.g., total tau), and other available biomarkers in ADNI will be used to predict these trajectories using machine learning. Specifically, we will use random forest analysis to detect important biomarker predictors in each of the stages of the AD spectrum.