| dc.contributor.author | Mahapatra, Tanmaya | |
| dc.date.accessioned | 2024-05-09T03:54:15Z | |
| dc.date.available | 2024-05-09T03:54:15Z | |
| dc.date.issued | 2020-07 | |
| dc.identifier.uri | https://pubmed.ncbi.nlm.nih.gov/32706673/ | |
| dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/14781 | |
| dc.description.abstract | Modern data-driven medical research provides new insights into the development and course of diseases and enables novel methods of clinical decision support. Clinical and translational data warehouses, such as Informatics for Integrating Biology and the Bedside (i2b2) and tranSMART, are important infrastructure components that provide users with unified access to the large heterogeneous data sets needed to realize this and support use cases such as cohort selection, hypothesis generation, and ad hoc data analysis. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Helmut Spengler | en_US |
| dc.subject | Computer Science | en_US |
| dc.subject | Docker | en_US |
| dc.subject | Cohort Selection | en_US |
| dc.subject | Data Warehouse | en_US |
| dc.subject | Extract-Transform-Load | en_US |
| dc.subject | Hypothesis Generation | en_US |
| dc.title | Enabling Agile Clinical and Translational Data Warehousing: Platform Development and Evaluation | en_US |
| dc.type | Article | en_US |
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