20 citations · 26 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
ACES: Automatic Cohort Extraction System for Event-Stream Datasets
Justin Xu, Jack Gallifant, Alistair E. W. Johnson +1
Reproducibility remains a significant challenge in machine learning (ML) for healthcare. Datasets, model pipelines, and even task or cohort definitions are often private in this fi…
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…
A Closer Look at AUROC and AUPRC under Class Imbalance
Matthew B. A. McDermott, Haoran Zhang, Lasse Hyldig Hansen +2
In machine learning (ML), a widespread claim is that the area under the precision-recall curve (AUPRC) is a superior metric for model comparison to the area under the receiver oper…