Investigating the Documentation of Electronic Cigarette Use in the Veteran Affairs Electronic Health Record: A Pilot Study

no code implementations • WS 2017 • Danielle Mowery, Brett South, Olga Patterson, Shu-Hong Zhu, Mike Conway

In this paper, we present pilot work on characterising the documentation of electronic cigarettes (e-cigarettes) in the United States Veterans Administration Electronic Health Record.

Epidemiology

Feature Studies to Inform the Classification of Depressive Symptoms from Twitter Data for Population Health

no code implementations • 28 Jan 2017 • Danielle Mowery, Craig Bryan, Mike Conway

In the second experiment, we observed that the optimal F1-score performance of top ranked features in percentiles variably ranged across classes e. g., fatigue or loss of energy (5th percentile, 288 features) to depressed mood (55th percentile, 3, 168 features) suggesting there is no consistent count of features for predicting depressive-related tweets.

General Classification

Towards Developing an Annotation Scheme for Depressive Disorder Symptoms: A Preliminary Study using Twitter Data

no code implementations • WS 2015 • Danielle Mowery, Craig Bryan, Mike Conway

Generating Patient Problem Lists from the ShARe Corpus using SNOMED CT/SNOMED CT CORE Problem List

no code implementations • WS 2014 • Danielle Mowery, Mindy Ross, Sumithra Velupillai, Stephane Meystre, Janyce Wiebe, Wendy Chapman