40 citations · 53 across the 15 of their papers we have counts for
8 papers · 1 filter
Machine Learning for Health symposium 2024 -- Findings track
Stefan Hegselmann, Helen Zhou, Elizabeth Healey +6
A collection of the accepted Findings papers that were presented at the 4th Machine Learning for Health symposium (ML4H 2024), which was held on December 15-16, 2024, in Vancouver,…
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…
Business Metric-Aware Forecasting for Inventory Management
Helen Zhou, Sercan O. Arik, Jingtao Wang
Time-series forecasts play a critical role in business planning. However, forecasters typically optimize objectives that are agnostic to downstream business goals and thus can prod…
Evaluating Model Performance in Medical Datasets Over Time
Helen Zhou, Yuwen Chen, Zachary C. Lipton
Machine learning (ML) models deployed in healthcare systems must face data drawn from continually evolving environments. However, researchers proposing such models typically evalua…
Model Evaluation in Medical Datasets Over Time
Helen Zhou, Yuwen Chen, Zachary C. Lipton
Machine learning models deployed in healthcare systems face data drawn from continually evolving environments. However, researchers proposing such models typically evaluate them in…
Domain Adaptation under Missingness Shift
Helen Zhou, Sivaraman Balakrishnan, Zachary C. Lipton
Rates of missing data often depend on record-keeping policies and thus may change across times and locations, even when the underlying features are comparatively stable. In this pa…
Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19
Helen Zhou, Cheng Cheng, Kelly J. Shields +4
With COVID-19 now pervasive, identification of high-risk individuals is crucial. Using data from a major healthcare provider in Southwestern Pennsylvania, we develop survival model…
Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes
Soorajnath Boominathan, Michael Oberst, Helen Zhou +2
In several medical decision-making problems, such as antibiotic prescription, laboratory testing can provide precise indications for how a patient will respond to different treatme…