550 citations · 963 across the 9 of their papers we have counts for
10 papers
Investigating Data Interventions for Subgroup Fairness: An ICU Case Study
Erin Tan, Judy Hanwen Shen, Irene Y. Chen
In high-stakes settings where machine learning models are used to automate decision-making about individuals, the presence of algorithmic bias can exacerbate systemic harm to certa…
Closing the Gap in High-Risk Pregnancy Care Using Machine Learning and Human-AI Collaboration
Hussein Mozannar, Yuria Utsumi, Irene Y. Chen +4
A high-risk pregnancy is a pregnancy complicated by factors that can adversely affect the outcomes of the mother or the infant. Health insurers use algorithms to identify members w…
Machine Learning for Health symposium 2022 -- Extended Abstract track
Antonio Parziale, Monica Agrawal, Shalmali Joshi +4
A collection of the extended abstracts that were presented at the 2nd Machine Learning for Health symposium (ML4H 2022), which was held both virtually and in person on November 28,…
Clustering Interval-Censored Time-Series for Disease Phenotyping
Irene Y. Chen, Rahul G. Krishnan, David Sontag
Unsupervised learning is often used to uncover clusters in data. However, different kinds of noise may impede the discovery of useful patterns from real-world time-series data. In…
Ethical Machine Learning in Health Care
Irene Y. Chen, Emma Pierson, Sherri Rose +3
The use of machine learning (ML) in health care raises numerous ethical concerns, especially as models can amplify existing health inequities. Here, we outline ethical consideratio…
Probabilistic Machine Learning for Healthcare
Irene Y. Chen, Shalmali Joshi, Marzyeh Ghassemi +1
Machine learning can be used to make sense of healthcare data. Probabilistic machine learning models help provide a complete picture of observed data in healthcare. In this review,…