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--- projects:workgroups:wg_meeting_01062016 [2016/01/06 17:01] – created anu_gururaj
+++ projects:workgroups:wg_meeting_01062016 [2016/03/07 22:48] (current) – anu_gururaj
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 ==== Attendees ====
+Hua Xu, Jon Duke, George Hripcsak, Karthik Natarajan, Anupama Gururaj, Mark Khayter, Min Jiang, Don Torok, Alexandre Yahi, Andrew Williams
 ==== Agenda ====
@@ Line 15: / Line 15: @@
 ===Minutes===
-  - Presentation
+  - General IRB document for use of clinical text and approval from all contributors, post online - Almost completed
-  - IRB for use of clinical text
+  - Collect minimum set of modifiers for all clinical entities that support use of rule to derive clinical concepts: Alex
-  - Clinical text data storage and representation schema
+      * cTAKES is being run on clinical notes programmatically. Alex will present the minimal model in the next meeting.
-  - NLP tools/pipelines for ETL
+  - Aggregate and share note-type metadata from various sources: Karthik
-  - Use cases, e.g, phenotyping for cohort selection using NLP outputs
+      * LOINC note type mapping would be a very useful resource. We should generate hierarchical representation of note-types as an ontology. Karthik will present his work to date at the next meeting.
-  - Discussion
+      * Existing ontology for note types to be shared : Vanderbilt (Hua) and Regenstrief (Jon)
+  - Simple search set up for MT samples: MinPresentation
+      * Presentation {{:projects:workgroups:clinical_text_search_engine_01_06.pdf|}}
+      * The interface being developed should present a summary with visualization for patients/notes.
+      * We will add Boolean query options to improve the search
+      * We will implement a Ranking algorithm
+      * Assign fake patient ID's to the notes to generate the visualization portion.
+      * Generate a program like Circe to define the patient cohort
+      * Next steps: How to move the data from textual searches stored in a table outside of OMOP to the OMOP?
+          * 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===
+  - Minimal Model Presentation - Alex
+  - Note-type mapping Presentation - Karthink
+  - Share existing ontologies from Vanderbilt (Hua) and Regenstrief (Jon)
+  - Share strategies for combining data from different searches - Jon
+  - Report on WG for commenting - Hua
+  - Wrappers for cTAKES and Metamap - Min
+  - Improvements to search engine set up using MT samples - Min
+  - Textual Data Representation - Discussion