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projects:workgroups:wg_meeting_02032016 [2016/03/07 21:36] anu_gururaj |
projects:workgroups:wg_meeting_02032016 [2016/03/07 22:03] anu_gururaj |
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===Minutes=== | ===Minutes=== | ||
- | - Minimal model presntation - Alex | + | - Minimal model presentation - Alex |
- | - | + | - the model is based on the SHARE-N model and adapted to the current data structure. This model incorporates other semantic types and all of the modifiers are not available in cTAKES yet. |
- | - Collect minimum set of modifiers for all clinical entities that support use of rule to derive clinical concepts: Alex | + | - the notes were processed from eMERGE cohort at Columbia with about 60,000 notes encompassing 1700 patients. The original patient number was 3200. |
- | * cTAKES is being run on clinical notes programmatically. Alex will present the minimal model in the next meeting. | + | - In theory, a set containing the combination of minimal modifiers can be generated. Practically, can we trust the data enough to add it into OHDSI tables? - only highest confidence data (with maximum PPV) should be added to the tables. |
- | - Aggregate and share note-type metadata from various sources: Karthik | + | - Next steps: |
- | * LOINC note type mapping would be a very useful resource. We should generate hierarchical representation of note-types as an ontology. Karthink will present his work to date at the next meeting. | + | - Look at the note sections to determine the errors. |
- | * Existing ontology for note types to be shared : Vanderbilt (Hua) and Regenstrief (Jon) | + | - Work with Sunny to generate the NLP outputs for the phenotyping data |
- | - Simple search set up for MT samples: MinPresentation | + | - Evaluate by comparisons with structured data |
- | * Presentation | + | - Make the system more robust |
- | * The interface being developed should present a summary with visualization for patients/notes. | + | - Generate a protocol and/or annotation guidelines |
- | * We will add Boolean query options to improve the search | + | - Share the data as a Gold standard with manually annotated CUIs |
- | * We will implement a Ranking algorithm | + | - Alex's script is to be tried on different datasets and evaluated across notes from different institutions |
- | * Assign fake patient ID's to the notes to generate the visualization portion. | + | - Identify minimal set of notes to work with when recommending to the OHDSI community |
- | * Generate a program like Circe to define the patient cohort | + | - Identify sets of concepts that are not reliable - negation is a very good example of this idea. |
- | * Next steps: How to move the data from textual searches stored in a table outside of OMOP to the OMOP? | + | - Continue discussion of NLP system evaluation across different sites |
- | * Structured searches from CDW and textual searches can be combined using existing strategies. Jon will share the slides of his presentation on combining data from different searches | + | |
- | * Run NLP on the ElasticSearch to extract information | + | |
- | - Wrappers for cTAKES and Metamap | + | |
- | - Report on the WG - Hua will generate and share with the members for comments | + | |
- | - The best ways to represent textual data need to be determined | + | |
===Action Items=== | ===Action Items=== | ||
- | - Minimal Model Presentation - Alex | ||
- Note-type mapping Presentation - Karthink | - Note-type mapping Presentation - Karthink | ||
- Share existing ontologies from Vanderbilt (Hua) and Regenstrief (Jon) | - Share existing ontologies from Vanderbilt (Hua) and Regenstrief (Jon) | ||
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- Improvements to search engine set up using MT samples - Min | - Improvements to search engine set up using MT samples - Min | ||
- Textual Data Representation - Discussion | - Textual Data Representation - Discussion | ||
+ | - NLP system evaluation across different sites - Discussion |