Description:
- Alzheimer's data harmonization
- Other healthcare big-data applications
Abstract
USC researchers have developed the system GAAIN Entity Mapper (GEM), which solves the data harmonization problem. GEM also consists of many proprietary methods and systems to achieve data harmonization and presentation. GEM is being developed further to reduce the human-in-the-loop requirement during reading and classifying data, and mapping data entities from known and unknown formats.
Benefit
- Reading and sorting data from known and unknown patient data sources
- Mapping entities to generate useful information
- Low cost presentation of useful information to healthcare professionals
Market Application
There is an abundance of Alzheimer’s disease related data from around the world. Harmonizing this data to make it useful information has been the challenge. This is because data is collected and presented in various ways in different parts of the world, and it requires specialized medical know-how to assist with mapping the data. Mapping such comparable data has been identified as the best chance researchers have to combat many such medical conditions plaguing our world today.
Publications
The GAAIN Entity Mapper: An Active-Learning System for Medical Data Mapping. Front Neuroinform. (2016).
Other
- Tested
- Know-how, and software system available