2 citations · 5 across the 10 of their papers we have counts for
6 papers · 1 filter
Rank-Constrained Adaptation for Reliable Real-World Performance
Abinitha Gourabathina, Hyewon Jeong, Teya Bergamaschi +2
Deep learning models trained to optimize average accuracy often exhibit systematic failures on particular subpopulations. In real-world settings like healthcare, the subpopulations…
Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding
Xiao Xiang, David Restrepo, Hyewon Jeong +2
Electronic health records (EHR) arrive masked. Clinicians order measurements selectively, and any patient table thus contains only a subset of the values that characterize the unde…
Identifying Differential Patient Care Through Inverse Intent Inference
Hyewon Jeong, Siddharth Nayak, Taylor Killian +1
Sepsis is a life-threatening condition defined by end-organ dysfunction due to a dysregulated host response to infection. Although the Surviving Sepsis Campaign has launched and ha…
MEDS-Tab: Automated tabularization and baseline methods for MEDS datasets
Nassim Oufattole, Teya Bergamaschi, Aleksia Kolo +4
Effective, reliable, and scalable development of machine learning (ML) solutions for structured electronic health record (EHR) data requires the ability to reliably generate high-q…
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang +40
The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between…
Event-Based Contrastive Learning for Medical Time Series
Hyewon Jeong, Nassim Oufattole, Matthew Mcdermott +4
In clinical practice, one often needs to identify whether a patient is at high risk of adverse outcomes after some key medical event. For example, quantifying the risk of adverse o…