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Related Experiment Video

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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

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Published on: January 8, 2020

Medical data transformation using rewriting.

Naveen Ashish¹, Arthur W Toga¹

¹Laboratory of Neuroimaging, Institute for Neuroimaging and Neuroinformatics, Keck School of Medicine of USC, University of Southern California Los Angeles, CA, USA.

Frontiers in Neuroinformatics

|March 10, 2015

Summary

This summary is machine-generated.

This study introduces a new system for transforming medical data into a unified format, crucial for Alzheimer's disease research. The system enhances data integration and query rewriting for efficient disease dataset analysis.

Keywords:

Alzheimer's disease datasets data integration data mapping query rewriting

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Area of Science:

Medical Informatics
Data Science
Computational Biology

Background:

Federating data across multiple providers is challenging.
Standardizing medical data is essential for large-scale research.
Alzheimer's disease research requires integrated datasets.

Purpose of the Study:

To present a system for declaratively transforming medical data into a common data model.
To support the Global Alzheimer's Association Innovative Neuroscience (GAAIN) project.
To improve data federation for Alzheimer's disease research.

Main Methods:

Leveraging state-of-the-art data integration and query rewriting techniques.
Developing new formalisms for broader data transformation tasks.
Implementing new execution methodologies for efficient data transformation.

Main Results:

A general-purpose data transformation system has been developed.
The system extends existing data integration technologies.
Efficient transformation methodologies are provided for disease datasets.

Conclusions:

The developed system facilitates data federation for Alzheimer's disease research.
The system's formalisms and methodologies enhance data transformation capabilities.
This work contributes to more effective analysis of multi-provider medical data.