Over the past couple of decades, the explosion of densely interconnected data has stimulated the research, development and adoption of graph database technologies. From early graph models to more recent native graph databases, the landscape of implementations has evolved to cover enterprise-ready requirements. Because of the interconnected nature of its data, the biomedical domain has been one of the early adopters of graph databases, enabling more natural representation models and better data integration workflows, exploration and analysis facilities. In this work, we survey the literature to explore the evolution, performance and how the most recent graph database solutions are applied in the biomedical domain, compiling a great variety of use cases. With this evidence, we conclude that the available graph database management systems are fit to support data-intensive, integrative applications, targeted at both basic research and exploratory tasks closer to the clinic.
The change norms adjusted for pertinent demographics and practice effects. The group with cognitive complaints displayed a trend toward cognitive decline compared to the normative group, with the A+T/N+ subgroup showing the most marked decline. This was observed in tests of episodic memory and cognitive flexibility/divided attention. Conclusions: We present 2-year cognitive change norms for adults between 41 and 84 years, adjusted for practice and demographics. A web-based change norm calculator is provided.
Key PointsQuestion: When we statistically adjust for relevant factors, how is cognitive change associated with Alzheimer's disease biochemical pathology? Findings: Using the norms for change developed in this study, we found that biomarkers indicating Alzheimer's disease were associated with cognitive decline in tests of memory and executive function. Importance: Our change norms can be used in the clinic or in research to detect cognitive decline that may be caused by early Alzheimer's disease or other relevant conditions. Next Steps: Future research could explore the usefulness of cognitive change norms when diagnosing mild cognitive impairment.
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