projects:workgroups:wg_meeting_02032016
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projects:workgroups:wg_meeting_02032016 [2016/03/07 21:42] anu_gururaj |
projects:workgroups:wg_meeting_02032016 [2016/03/09 20:31] (current) anu_gururaj |
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| ==== Attendees ==== | ==== Attendees ==== | ||
| - | Hua Xu, Jon Duke, George Hripcsak, Karthik Natarajan, Anupama Gururaj, Mark Khayter, Min Jiang, Alexandre Yahi, Noemie Elhadad, Juan M Banda, Olga Patterson, Lian | + | Hua Xu, Jon Duke, George Hripcsak, Karthik Natarajan, Anupama Gururaj, Mark Khayter, Min Jiang, Alexandre Yahi, Noemie Elhadad, Juan M Banda, Olga Patterson, Lian Hu |
| ==== Agenda ==== | ==== Agenda ==== | ||
| + | |||
| + | {{:projects:workgroups:nlp_wg_meeting_02032016_final.pdf|}} | ||
| - Minimal Model Presentation – Alex | - Minimal Model Presentation – Alex | ||
| Line 20: | Line 22: | ||
| ===Minutes=== | ===Minutes=== | ||
| - | - Minimal model presentation - 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. | - 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. | ||
| - the notes were processed from eMERGE cohort at Columbia with about 60,000 notes encompassing 1700 patients. The original patient number was 3200. | - the notes were processed from eMERGE cohort at Columbia with about 60,000 notes encompassing 1700 patients. The original patient number was 3200. | ||
| - | - | + | - 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. |
| - | - Collect minimum set of modifiers for all clinical entities that support use of rule to derive clinical concepts: Alex | + | - Next steps: |
| - | * cTAKES is being run on clinical notes programmatically. Alex will present the minimal model in the next meeting. | + | - Look at the note sections to determine the errors. |
| - | - Aggregate and share note-type metadata from various sources: Karthik | + | - Work with Sunny to generate the NLP outputs for the phenotyping data |
| - | * 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. | + | - Evaluate by comparisons with structured data |
| - | * Existing ontology for note types to be shared : Vanderbilt (Hua) and Regenstrief (Jon) | + | - Make the system more robust |
| - | - Simple search set up for MT samples: MinPresentation | + | - Generate a protocol and/or annotation guidelines |
| - | * Presentation | + | - Share the data as a Gold standard with manually annotated CUIs |
| - | * The interface being developed should present a summary with visualization for patients/notes. | + | - Alex's script is to be tried on different datasets and evaluated across notes from different institutions |
| - | * We will add Boolean query options to improve the search | + | - Identify minimal set of notes to work with when recommending to the OHDSI community |
| - | * We will implement a Ranking algorithm | + | - Identify sets of concepts that are not reliable - negation is a very good example of this idea. |
| - | * Assign fake patient ID's to the notes to generate the visualization portion. | + | - Continue discussion of NLP system evaluation across different sites |
| - | * Generate a program like Circe to define the patient cohort | + | - The NLP-WG will meet on second Wednesday of every month |
| - | * 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=== | ===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 | ||
| Line 53: | Line 48: | ||
| - 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_02032016.1457386959.txt.gz · Last modified: 2016/03/07 21:42 by anu_gururaj
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