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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.
Hua Xu OHDSI Collaborator Bio
Vipina K Keloth
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.
Participants | ||
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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 |
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