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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 - October 13, 2021 (as part of the WG meeting)
Title: Harnessing Big Data for Population Health: Advancing NLP Techniques to Extract Social-Behavioral Risk Factors from Free Text within Large Electronic Health Record Systems
Abstract: Social and Behavioral Determinants of Health (SBDH) are powerful drivers of future well-being of individuals, but the clinical community rarely has access to standardized tools to systematically incorporate SBDH into clinical research and decision-making. To address this, we have been creating fundamental resources to systematically identify SBDH from within health records. We incorporate a wide range data sources such as coded clinical data (ICD codes), encoded questionnaires, and annotated texts corpora, and we apply a variety of NLP and AI methods such as heuristic-based natural language inference, conventional machine learning, and contextual neural network models. At the same time, we also focus on the dissemination of our methods and collaborating with external partners to ensure the generalizability of our models across various health systems. Results for heuristic-based, deep learning and ensemble models are promising and we have successfully validated our models on external partners sites.
Presenter: Dr. Masoud Rouhizadeh
Masoud Rouhizadeh is an Assistant Professor in the University of Florida College of Pharmacy, Department of Pharmaceutical Outcomes, under the AI in the Health Sciences Initiative.
The primary focus of Dr. Rouhizadeh’s research involves applying machine learning and natural language processing methods for identifying clinical concepts from unstructured text and converting them into structured data. Another major part of his research has been developing clinical ontologies and lexical resources, as well as computational models for identifying social and behavioral determinants of health.
Before joining the UF, Dr. Rouhizadeh was a Faculty Instructor at Biomedical Informatics and Data Science and the Natural Language Processing lead at the Institute for Clinical and Translational Research at the Johns Hopkins University School of Medicine. Prior to JHU, he was a postdoctoral fellow at the University of Pennsylvania’s World Well-Being Project and then at the Penn Institute for Biomedical Informatics. He obtained his Master’s and Ph.D. in Computer Science and Engineering from Oregon Health and Science University and his Master’s in Human Language Technology from the University of Trento, Italy.
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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