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Description

Abstract: tranSMART is an open source translational research platform and provides an integrated data solution for clinical data, omics data, and image data. However, the current tranSMART data architecture can only handle structure data. End user cannot access the rich information from unstructured data, such as clinical notes, directly. Natural Language Processing (NLP) is a powerful technology to retrieve meaningful information from unstructured text. Current NLP implementations focus on information extraction during data curation stage. End user can only access those pre-defined and pre-processed static NLP outputs. Here, we present an implementation of a NLP-based data analysis module for tranSMART. It allows end users to customize the NLP query, generate and validate the results dynamically.

Learning Objective 1: System integration for open source translational research platfrom.

Learning Objective 2 (Optional): Real time Nature Langurage Processing Analysis module for translational research.

Authors:

Haiqing Li (Presenter)
City of Hope National Medical Center

Yingyan Wu, City of Hope National Medical Center
Ningrong Ye, City of Hope National Medical Center
Hongzhi li, City of Hope National Medical Center
Susan Hmwe, City of Hope National Medical Center
Xiaoping Yi, City of Hope National Medical Center
Taihao Jin, City of Hope National Medical Center
xu zhang, City of Hope National Medical Center
Bihong Chen, City of Hope National Medical Center
Weizhong Zhu, City of Hope National Medical Center

Presentation Materials:

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