projects:workgroups:wg_meeting_11042015
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projects:workgroups:wg_meeting_11042015 [2015/11/30 16:48] anu_gururaj |
projects:workgroups:wg_meeting_11042015 [2016/01/06 20:47] (current) anu_gururaj [Agenda] |
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| ===Minutes=== | ===Minutes=== | ||
| + | - Presentation {{:projects:workgroups:nlp_wg_meeting_11042015_final.pdf|}} | ||
| -Updates from Annual meeting | -Updates from Annual meeting | ||
| * Extensive interest from the OHDSI community with reference to the text processing aspect. During the meeting, suggestions for improvements in the current projects were received. | * Extensive interest from the OHDSI community with reference to the text processing aspect. During the meeting, suggestions for improvements in the current projects were received. | ||
| Line 28: | Line 29: | ||
| -NLP tools/pipelines for ETL | -NLP tools/pipelines for ETL | ||
| * The plan is to develop a set of wrappers for multiple NLP tools (currently cTAKES and MetaMap) for conversion of output to the OHDSI textual data schema. | * The plan is to develop a set of wrappers for multiple NLP tools (currently cTAKES and MetaMap) for conversion of output to the OHDSI textual data schema. | ||
| - | * In order to get an idea of the updates in cTAKES< need to invite Guergana Savova to present and do a demo of cTAKES during the January call. | + | * In order to get an idea of the updates in cTAKES, need to invite Guergana Savova to present and do a demo of cTAKES during the January call. |
| * In order to prioritize the work, focus on positive concepts first for high confidence extraction of NER from text. | * In order to prioritize the work, focus on positive concepts first for high confidence extraction of NER from text. | ||
| -Use cases, e.g, phenotyping for cohort selection using NLP outputs | -Use cases, e.g, phenotyping for cohort selection using NLP outputs | ||
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| - set of data elements or features on which an algorithm functions | - set of data elements or features on which an algorithm functions | ||
| - formulation of the phenotype definition | - formulation of the phenotype definition | ||
| - | * Unordered List Item | + | * In order to represent the NLP output, query-based phenotyping will be the first focus of the group. |
| + | * For machine-learning based algorithms, the NLP output will be accessed outside of the CDM | ||
| + | * Is ElasticSearch a good first step in this area? ES should be considered here as a tool more for cohort building and selection rather than phenotyping. For this purpose, it is a good starting point. | ||
| + | * Finding patients for clinical trials will be used as a usecase here. The ES could serve as an explorer for feature selection in the phenotyping process. | ||
| + | * Action item: Simple search set up for MT samples by next meeting by Min. | ||
| + | * Use MIMICII and MIMICIII as demo datasets for the tools being developed by the group | ||
| -Discussion | -Discussion | ||
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| + | ===Action Items=== | ||
| + | |||
| + | - General IRB document for use of clinical text and approval from all contributors, post online - Anu | ||
| + | - Collect minimum set of modifiers for all clinical entities that support use of rule to derive clinical concepts: Alex | ||
| + | - Aggregate and share note-type metadata from various sources: Karthik | ||
| + | - Simple search set up for MT samples: Min | ||
projects/workgroups/wg_meeting_11042015.1448902121.txt.gz · Last modified: 2015/11/30 16:48 by anu_gururaj
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