Scholar
Emily Getzen
Google Scholar ID: 4kVLYxIAAAAJ
University of Pennsylvania
Citations & Impact
Citations
517
H-index
12
i10-index
14
Publications
20
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- ['Paper "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" accepted to AMIA Annual Symposium (July 2023).', 'Paper "Informative Missingness: What can we learn from patterns in missing laboratory data in the electronic health record?" accepted by Journal of Biomedical Informatics (January 2023).', 'Paper "Mining for Equitable Health: Assessing the Impact of Missing Data in Electronic Health Records" highlighted by Penn's Leonard Davis Institute of Health Economics (February 2023).', 'Recipient of ASA Biopharmaceutical Section Student Scholarship Award (May 2023).', 'Recipient of the 2023 American Statistical Association Gertrude M. Cox Scholarship (March 2023).', 'Recipient of the ASA Philadelphia Chapter Graduate Student Award (February 2023).', 'Best Poster Award at the Second Penn Conference on Big Data in Biomedical and Population Health Sciences (September 2022).', 'Team received Honorable Mention in NIH Long COVID Computational Challenge (L3C) (April 2023).']
Background
- 5th-year PhD student in Biostatistics at the University of Pennsylvania, graduating Spring 2024.
- Research lies at the intersection of machine learning, statistics, and medicine.
- Focuses on developing deep learning methods for multimodal EHR data—handling both structured and unstructured data sampled at irregular time intervals.
- Develops methods to assess the impact of healthcare access on algorithmic fairness.
- Aims to build trustworthy and equitable deep learning models that fuse multimodal health data (imaging, 'omics, EHRs, wearables) for disease prediction to improve healthcare accessibility and empower individuals.
Co-authors