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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.

Project Lead

Project Coordinator

Vipina K Keloth

OHDSI NLP WG Monthly Meeting

When: Second Wednesday of every month at 1 PM - 2 PM CT

Where: Click here to join the meeting

Monthly Research Webinar: Upcoming - August 11, 2021 (as part of the WG meeting)

Title: Leveraging longitudinal and multi-modal EHR in Survival Analysis
Abstract: Survival analysis is a fundamental statistical tool that predicts the time of an event. It has multiple healthcare applications in areas, such as hospitalization and patient mortality. Clinicians predict patient outcomes by heterogeneous modalities (e.g., text, images, and lab values). Such data poses significant challenges for traditional survival analysis techniques. In this talk, we present our effort to expand the survival analysis using multimodal, longitudinal EHR data. Our results indicate that extracted high-dimensional features from text and image provide complementary information in addition to structured EHR, and incorporating longitudinal data is useful in time-to-event prediction.

Presenter: Dr. Yifan Peng
Dr. Peng is an assistant professor at the Department of Population Health Sciences at Weill Cornell Medicine. His main research interests include BioNLP and medical image analysis, such as named entity recognition, information extraction, and eye disease diagnosis and prognosis. Before joining Cornell Medicine, Dr. Peng was a research fellow at the National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH). He obtained his Ph.D. degree from the University of Delaware. During his doctoral training, he investigated applications of machine learning in biomedical relation extraction, with a focus on deep analysis of the linguistic structures of biomedical texts.

Ongoing Projects

TBD

Past Projects

TBD

Participants

Participants
Hua Xu Abraham Hartzema Feifan Liu
Anupama Gururaj David Sontag Paris Nicolas
Nigam Shah Arnab Bose Mark Dredze
Noemie Elhadad Lian Hu Masoud Rouhizadeh
Jon Duke Jan A Kors Malcolm McRoberts
Alexandre Yahi J van Der Lei Nishanth Parameshwar Pavinkurve
Thomas Ginter Peter R Rijnbeek Carol Friedman
Olga Patterson Vivienne Zhu Miao Chen
George Hripsack Bob Patterson Jianlin Shi
Vojtech Huser Michael Gurley Vassilis Koutkias
Mark Khayter Xiaoling Chen Dan Schlegel
Karthik Natarajan Hongfang Liu Mark V Mai
Min Jiang Hong Yu Todd Lingren
Scott DuVall Stephane Meystre Jose Posada
Xiao Dong Timothy Miller Andrew E Williams
Ning Shang Wendy Chapman Vignesh Srinivasan
Jessie Tenenbaum Elizabeth Marshall Yuan Luo
Kathleen Nogueira Noa Palmon Kelly Peterson
Chris Ryan Danielle Bitterman Jimyung Park
Kate Weber Alexander Sivura Patrick Alba
Tarun Xi Yang Meliha Yetisgen
T.M. Seinen Jiang Bian Xiyu Ding
Georgina Kennedy Yaoyun Zhang Rui Zhang
Paul Heider

Upcoming Meeting Dates (2021)

  • August 11
  • September 8
  • October 13
  • November 10
  • December 8

Repository

Past WG meetings (Agenda/Minutes/Recordings)

Microsoft Teams meeting

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Click here to join the meeting

Learn More

projects/workgroups/nlp-wg.1628450659.txt.gz · Last modified: 2021/08/08 19:24 by vipina