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projects:workgroups:wg_meeting_02032016 [2016/03/07 21:36]
anu_gururaj
projects:workgroups:wg_meeting_02032016 [2016/03/07 22:50]
anu_gururaj
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 ==== Agenda ==== ==== Agenda ====
 +
 +{{:​projects:​workgroups:​nlp_wg_meeting_02032016_final.pdf|}}
  
   - Minimal Model Presentation – Alex   - Minimal Model Presentation – Alex
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 ===Minutes=== ===Minutes===
  
-  - Minimal model presntation ​- Alex +  - Minimal model presentation ​- Alex {{:​projects:​workgroups:​ohdsi_nlp_wg_yahi.pdf|}} 
-        -  +        - 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, ​set containing the combination ​of minimal modifiers can be generatedPractically,​ can we trust the data enough ​to add it into OHDSI tables? - only highest confidence data (with maximum PPVshould be added to the tables. 
-  Aggregate and share note-type metadata ​from various sources: Karthik +        Next steps
-      * LOINC note type mapping would be very useful resource. We should generate hierarchical representation ​of note-types as an ontologyKarthink 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 samplesMinPresentation +          - 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 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 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 +   ​- The NLP-WG will meet on second Wednesday of every month
-          ​* 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 - Karthik
-  ​- Note-type mapping Presentation - Karthink+
   - Share existing ontologies from Vanderbilt (Hua) and Regenstrief (Jon)   - Share existing ontologies from Vanderbilt (Hua) and Regenstrief (Jon)
   - Share strategies for combining data from different searches - Jon   - Share strategies for combining data from different searches - 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
projects/workgroups/wg_meeting_02032016.txt · Last modified: 2016/03/09 20:31 by anu_gururaj