Observational Health Data Sciences and Informatics

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====== OHDSI Natural Language Processing Working Group ======

==== Objective ====

The primary goal of the NLP working group is to promote the use of textual information from Electronic Health Records (EHRs) for observational studies under the OHDSI umbrella. To facilitate this objective, the group will develop methods and software that can be implemented to utilize clinical text for studies by the OHDSI community.

==== Workgroup Lead ====

[[https://www.ohdsi.org/who-we-are/collaborators/hua-xu/|Hua Xu]]\\



==== Project Coordinator ====

 [[vipina.kuttichikeloth@yale.edu | Vipina K. Keloth ]]

==== OHDSI NLP WG Monthly Meeting ====
**When:** Second Wednesday of every month at 1 PM - 2 PM CT

**Where:** [[https://teams.microsoft.com/dl/launcher/launcher.html?url=%2F_%23%2Fl%2Fmeetup-join%2F19%3Acd9841fec6df4f3d8eb6a6bf49ea305f%40thread.tacv2%2F1610663053273%3Fcontext%3D%257b%2522Tid%2522%253a%2522a30f0094-9120-4aab-ba4c-e5509023b2d5%2522%252c%2522Oid%2522%253a%252200626e72-b11c-482a-9dc4-d8eff51c5e5f%2522%257d%26anon%3Dtrue&type=meetup-join&deeplinkId=42431bac-788d-4a7b-8531-5eb2612224a6&directDl=true&msLaunch=true&enableMobilePage=true&suppressPrompt=true|Click here to join the meeting]]

**Monthly Meeting:** Upcoming - May 9, 2023

**Agenda**

 1) Presentation - **Nic Dobbins** (Principal Solutions Architect at UW Medicine Research IT; PhD Candidate in biomedical informatics at the University of Washington)\\
**Title:** LeafAI: query generator for clinical cohort discovery rivaling a human programmer\\
**Abstract:**  Identifying study-eligible patients within clinical databases is a critical step in clinical research. However, accurate query design typically requires extensive technical and biomedical expertise. We sought to create a system capable of generating data model-agnostic queries while also providing novel logical reasoning capabilities for complex clinical trial eligibility criteria. We incorporated hybrid deep learning and rule-based modules for these, as well as a knowledge base of the Unified Medical Language System (UMLS) and linked ontologies. To enable data-model agnostic query creation, we introduce a novel method for tagging database schema elements using UMLS concepts. To evaluate our system, called LeafAI, we compared the capability of LeafAI to a human database programmer to identify patients who had been enrolled in 8 clinical trials conducted at our institution. We measured performance by the number of actual enrolled patients matched by generated queries. LeafAI matched a mean 43% of enrolled patients with 27,225 eligible across 8 clinical trials, compared to 27% matched and 14,587 eligible in queries by a human database programmer. The human programmer spent 26 total hours crafting queries compared to several minutes by LeafAI. Finally, we introduce a novel multimodal user interface for interaction with LeafAI.\\

2) Updates on the progress of ongoing studies
  - SDoH
  - Psychiatry
  - Oncology
3) NLP book chapter


==== Ongoing Projects ====

  * Note type normalization
  * Social Determinants of Health
  * Psychiatry - NLP for capturing administration of neuropsychiatric scales and their scores
  * Oncology - NLP for getting oncology data using Tumor Reg data as a gold standard for assessing the information obtained through the NLP algorithm
  * Book of OHDSI NLP Chapter

==== Past Projects ====

  * Note_NLP table
  * COVID-19 testing normalization (TestNorm)
  * Note type
  * NLP tools: NLP Wrappers; THEIA; Ananke
==== Participants ====

A noncomprehensive list of participants: [[ Click here ]]

==== Upcoming Meeting Dates (2023) ====

  * June 14
  * July 12
  * August 9
  * September 13
  * October 11
  * November 8
  * December 13

==== Repository ====

  * NLP Tools in OHDSI GitHub [[https://github.com/OHDSI/NLPTools]]
  * OHDSIananke [[https://github.com/thepanacealab/OHDSIananke]]





==== Past WG meetings (Agenda/Minutes/Recordings) ====
**2023**\\
  -[[WG_meeting_may_10_2023]]
  -[[WG_meeting_apr_12_2023]]
  -[[WG_meeting_mar_08_2023]]
  -[[WG_meeting_feb_08_2023]]
  -[[WG_meeting_jan_11_2023]]

**2022**\\
  -[[WG_meeting_dec_14_2022]]
  -[[WG_meeting_nov_09_2022]]
  -[[WG_meeting_sep_14_2022]]
  -[[WG_meeting_aug_10_2022]]
  -[[WG_meeting_jun_08_2022]]
  -[[WG_meeting_may_11_2022]]
  -[[WG_meeting_apr_13_2022]]
  -[[WG_meeting_mar_09_2022]]
  -[[WG_meeting_feb_09_2022]]
  -[[WG_meeting_jan_12_2022]]

**2021**\\
  -[[WG_meeting_dec_08_2021]]
  -[[WG_meeting_nov_10_2021]]
  -[[WG_meeting_oct_13_2021]]
  -[[WG_meeting_sep_08_2021]]
  -[[WG_meeting_aug_11_2021]]

**2019**\\
  -[[WG_meeting_10092019]]
  -[[WG_meeting_09112019]]
  -[[WG_meeting_08142019]]
  -[[WG_meeting_07102019]]
  -[[WG_meeting_05082019]]
  -[[WG_meeting_04102019]]
  -[[WG_meeting_03132019]]
  -[[WG_meeting_02132019]]
  -[[WG_meeting_01092019]]
**2018**\\
  -[[WG_meeting_11142018]]
  -[[WG_meeting_09122018]]
  -[[WG_meeting_06132018]]
  -[[WG_meeting_05092018]]
  -[[WG_meeting_04142018]]
  -[[WG_meeting_03142018]]
  -[[WG_meeting_02142018]]
  -[[WG_meeting_01102018]]

**2017**\\
  -[[WG_meeting_12122017]]
  -[[WG_meeting_10112017]]
  -[[WG_meeting_09132017]]
  -[[WG_meeting_07122017]]
  -[[WG_meeting_06142017]]

**2016**\\
  -[[WG_meeting_04202016]]
  -[[WG_meeting_04132016]]
  -[[WG_meeting_03092016]]
  -[[WG_meeting_02032016]]
  -[[WG_meeting_01062016]]

**2015**\\
  -[[WG_meeting_11042015]]
  -[[projects:workgroups:minutes|WG_meeting_10072015]]

===== Microsoft Teams meeting =====


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