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NLP Detection of Mortality Information from Publicly Available Data Using Deep Learning Modeling

Basic Details
Date
Type
Presentation
Description

This poster outlines the design and implementation of a natural language processing (NLP) pipeline that can identify and extract the date of death, date of birth, and name of the deceased from multiple publicly available sources. 

It was presented at the 39th International Conference on Pharmacoepidemiology and Therapeutic Risk Management. 

Materials

NLP Detection of Mortality Information from Publicly Available Data Using Deep Learning Modeling 

Information
Host

International Society for Pharmacoepidemiology

Related Assessment(s)
Augmenting Date of Death & Cause of Death Ascertainment in Sentinel
Presenter(s)

Mohammed A. Al-Garadi, Michael E. Matheny, Rishi J Desai, Mirza S. Khan, Shirley V. Wang, Judith C. Maro, Candace C. Fuller , Kueiyu Joshua Lin, José J. Hernández-Muñoz, Aida Kuzucan, Xi Wang, Jill M. Whitaker, Jessica A. Deere, Michael F. McLemore, Dax Westerman, Josh Osmanski, Ruth Reeves