The long term goal of the Data Management Core is to develop and maintain a mechanism to support the computer, data processing, experimental design and data analysis needs for investigators engaged in the long-term study of Alzheimer's Disease. Research projects fail to thrive for many reasons. One such reason is the failure to focus sufficient attention on the often times tedious process of monitoring the acquisition and processing of information. Valid conclusions are virtually impossible when based upon unreliable or faulty data. Considerable care is necessary in attending to the details of complete data collection, data movement, verification, storage and processing as well as details of experimental design and analysis. We have detailed a mechanism to collect, transfer and process data obtained from diverse sites in such a way s to maximize its reliability and timely processing while minimizing the problems introduced by data missing as a result of an inappropriate or careless processing or collection. We have also taken care to insure its long-term safety. Considerable effort has been allocated toward the goal of processing of complete and reliable information. We have provided for assisting in the intemal monitoring of data reliability and standardization studies, within the clinical core, and the planning of analytic strategies. Technical support in processing of laboratory data and image analysis has been provided for those investigators with special needs. We have taken care to allow for the expansion of our support to new projects and investigators in an orderly and coherent manner. Finally, to enhance the communication among the investigators we have established several mechanisms for the transfer of information to each of the remote sites.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Center Core Grants (P30)
Project #
5P30AG008017-03
Application #
3790297
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
3
Fiscal Year
1992
Total Cost
Indirect Cost
Name
Oregon Health and Science University
Department
Type
DUNS #
009584210
City
Portland
State
OR
Country
United States
Zip Code
97239
Burke, Shanna L; Hu, Tianyan; Fava, Nicole M et al. (2018) Sex differences in the development of mild cognitive impairment and probable Alzheimer's disease as predicted by hippocampal volume or white matter hyperintensities. J Women Aging :1-25
Wang, Qi; Guo, Lei; Thompson, Paul M et al. (2018) The Added Value of Diffusion-Weighted MRI-Derived Structural Connectome in Evaluating Mild Cognitive Impairment: A Multi-Cohort Validation1. J Alzheimers Dis 64:149-169
Teipel, Stefan; König, Alexandra; Hoey, Jesse et al. (2018) Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia. Alzheimers Dement 14:1216-1231
Wang, Tingyan; Qiu, Robin G; Yu, Ming (2018) Predictive Modeling of the Progression of Alzheimer's Disease with Recurrent Neural Networks. Sci Rep 8:9161
Agogo, George O; Ramsey, Christine M; Gnjidic, Danijela et al. (2018) Longitudinal associations between different dementia diagnoses and medication use jointly accounting for dropout. Int Psychogeriatr 30:1477-1487
Wardzala, Casia; Murchison, Charles; Loftis, Jennifer M et al. (2018) Sex differences in the association of alcohol with cognitive decline and brain pathology in a cohort of octogenarians. Psychopharmacology (Berl) 235:761-770
Alosco, Michael L; Sugarman, Michael A; Besser, Lilah M et al. (2018) A Clinicopathological Investigation of White Matter Hyperintensities and Alzheimer's Disease Neuropathology. J Alzheimers Dis 63:1347-1360
Brent, Robert J (2018) Estimating the monetary benefits of medicare eligibility for reducing the symptoms of dementia. Appl Econ 50:6327-6340
Besser, Lilah; Kukull, Walter; Knopman, David S et al. (2018) Version 3 of the National Alzheimer's Coordinating Center's Uniform Data Set. Alzheimer Dis Assoc Disord 32:351-358
Deming, Yuetiva; Dumitrescu, Logan; Barnes, Lisa L et al. (2018) Sex-specific genetic predictors of Alzheimer's disease biomarkers. Acta Neuropathol 136:857-872

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