Publications

My research lies at the intersection of machine learning, statistics, and medicine. I primarily focus on the development of deep learning methods for complex electronic health records–this involves analysis of structured and unstructured multimodal and irregular time series data.

Mining for equitable health: Assessing the impact of missing data in electronic health records

Leveraging informative missing data to learn about acute respiratory distress syndrome and mortality in long-term hospitalized COVID-19 patients throughout the years of the pandemic

Amelia Tan*, Emily Getzen*, Meghan Hutch, Zachary Strasser, Alba Guiterrez-Sacristan, Trang Le, Arianna Dagliati, Michele Morris, David A Hanauer, Bertrand Moal, Clara-Lea Bonzel, William Yuan, Lorenzo Chiudinelli, Priam Das, Harrison G Zhang, Bruce J Aronow, Paul Avillach, Gabriel Brat, Tianxi Cai, Chuan Hong, William La Cava, He Hooi Will Loh, Yuan Luo, Shawn Murphey, Kee Yuan Hgiam, Gilbert S Omenn, Lav P Patel, Malarkodi Samayamuthu, Emily Shriver, Zahra Shakeri Hossein Abad, Byorn W L Tan, Shyam Visweswaran, Xuan Wang, Griffin M Weber, Zongqi Xia, Bertrand Verdy, COVID-19 by EHR (4CE), Qi Long, Danielle Mowery, John Homes. 

*denotes joint first authorship

Journal of Biomedical Informatics. Link to paper

Mining for Health: A Comparison of Word Embedding Methods for Analysis of EHRs Data 

Emily Getzen, Yucheng Yuan, Lyle Ungar, Qi Long

Accepted for publication in Precision Medicine: Methods and Applications. Link to paper

Mental health among head and neck surgeons in Brazil during the COVID-19 pandemic: A national study

Alyssa M. Civantos*, Antonio Bertelli, Antonio Goncalves, Emily Getzen, Changgee Chang, Qi Long, Karthik Rajasekaran

American Journal of Otolaryngology. Link to paper