Extracting Detailed Tobacco Exposure From The Electronic Health Record
Lung cancer is the leading cause of cancer-related death in the United States and worldwide. Natural language processing (NLP) tools exist to determine smoking status (ever-smoker vs. never-smoker) from electronic health record data, but no system to date extracts detailed smoking data needed to ass...
Main Author: | Osterman, Travis John |
---|---|
Other Authors: | Josh Denny, M.D., M.S. |
Format: | Others |
Language: | en |
Published: |
VANDERBILT
2017
|
Subjects: | |
Online Access: | http://etd.library.vanderbilt.edu/available/etd-07142017-193150/ |
Similar Items
-
Efficient Development of Electronic Health Record Based Algorithms to Identify Rheumatoid Arthritis
by: Carroll, Robert James
Published: (2011) -
Learning the State of Patient Care and Opportunities for Improvement from Electronic Health Record Data with Applications in Breast Cancer Patients
by: Harrell, Morgan Rachel
Published: (2017) -
Defining Phenotypes, Predicting Drug Response, and Discovering Genetic Associations in the Electronic Health Record with Applications in Rheumatoid Arthritis
by: Carroll, Robert James
Published: (2014) -
A PROCESS MODELING STRATEGY TO LEARN ISCHEMIC STROKE TREATMENT PATTERNS FROM ELECTRONIC MEDICAL RECORDS
by: Sulieman, Lina Mahmoud
Published: (2014) -
A framework for accurate, efficient private record linkage
by: Durham, Elizabeth Ashley
Published: (2012)