Name
Title | ||
|---|---|---|
An Associative Memory Model for Integration of Fragmented Research Data and Identification of Treatment Correlations in Breast Cancer Care. |
Abstract | ||
|---|---|---|
A major challenge in advancing scientific discoveries using data-driven clinical research is the fragmentation of relevant data among multiple information systems. This fragmentation requires significant data-engineering work before correlations can be found among data attributes in multiple systems. In this paper, we focus on integrating information on breast cancer care, and present a novel computational approach to identify correlations between administered drugs captured in an electronic medical records and biological factors obtained from a tumor registry through rapid data aggregation and analysis. We use an associative memory (AM) model to encode all existing associations among the data attributes from both systems in a high-dimensional vector space. The AM model stores highly associated data items in neighboring memory locations to enable efficient querying operations. The results of applying AM to a set of integrated data on tumor markers and drug administrations discovered anomalies between clinical recommendations and derived associations. |
Year | Venue | Keywords |
|---|---|---|
2015 | AMIA | Associative memory,breast cancer treatment,correlation,data integration,electronic medical record,tumor registry |
Field | DocType | Volume |
Data science,Information system,ENCODE,Content-addressable memory,Breast cancer,Computer science,Medical record,Data aggregator,System integration | Conference | 2015 |
Citations | PageRank | References |
1 | 0.40 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ashis Gopal Banerjee | 1 | 202 | 17.17 |
| Mridul Khan | 2 | 2 | 1.22 |
| John Higgins | 3 | 1 | 0.40 |
| Annarita Giani | 4 | 1 | 0.73 |
| Amar K. Das | 5 | 420 | 51.09 |