Background: Dementia or other significant cognitive impairment (SCI) are often comorbid with other chronic diseases. To promote collaborative research on the intersection of these conditions, we compiled a systematic inventory of major data resources.
Methods: Large data sets measuring dementia and/or cognition and chronic conditions in adults were included in the inventory. Key features of the resources were abstracted including region, participant sociodemographic characteristics, study design, sample size, accessibility, and available measures of dementia and/or cognition and comorbidities.
Results: 117 study data sets were identified; 53% included clinical diagnoses of dementia along with valid and reliable measures of cognition. Most (79%) used longitudinal cohort designs and 41% had sample sizes greater than 5000. Approximately 47% were European-based, 40% were US-based, and 11% were based in other countries.
Conclusions: Many high-quality data sets exist to support collaborative studies of the effects of dementia or SCI on chronic conditions and to inform the development of evidence-based disease management programs.
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http://dx.doi.org/10.1016/j.jalz.2014.07.002 | DOI Listing |
Alzheimers Dement
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German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
Numerous drugs (including disease-modifying therapies, cognitive enhancers and neuropsychiatric treatments) are being developed for Alzheimer's and related dementias (ADRD). Emerging neuroimaging modalities, and genetic and other biomarkers potentially enhance diagnostic and prognostic accuracy. These advances need to be assessed in real-world studies (RWS).
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Ecole Nationale Supérieure de Chimie de Paris, Université PSL, CNRS, Institute of Chemistry for Life and Health Sciences, 75 005 Paris, France.
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Tabular data, spreadsheets organized in rows and columns, are ubiquitous across scientific fields, from biomedicine to particle physics to economics and climate science. The fundamental prediction task of filling in missing values of a label column based on the rest of the columns is essential for various applications as diverse as biomedical risk models, drug discovery and materials science. Although deep learning has revolutionized learning from raw data and led to numerous high-profile success stories, gradient-boosted decision trees have dominated tabular data for the past 20 years.
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Department of American Culture, University of Michigan, Ann Arbor, USA.
We present a new national data set of historical sundown towns in the United States linked to contemporary spatial information - i.e., the Historical Sundown Towns Linked to US Census Geographies database.
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Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, F-21000, Dijon, France.
Microbiological datasets and associated environmental parameters from the French soil quality monitoring network (RMQS) offer an opportunity for long-term and large-scale soil quality monitoring. Soils supply important ecosystem services e.g.
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